Message&from&the&General&and&Program&Chairs&wacv16.wacv.net/wp-content/uploads/2016/02/WACV... · Message&from&the&General&and&Program&Chairs& 1!! Welcome’to’Lake’Placid,’NY,’and’the’16th’edition’of’

Message from the General and Program Chairs

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Welcome to Lake Placid, NY, and the 16th edition of WACV (renamed as IEEE Winter Conference on Applications of Computer Vision, since 2014). In addition to the main three-‐day program of oral and poster presentations, keynote talks and social functions, WACV 2016 has a number of co-‐located events, including three workshops and two tutorials. WACV 2016 is a two-‐track conference in which each accepted paper will be presented as a short oral and a poster.

For WACV 2016, two separate tracks were introduced for submissions, one for algorithms and the other for systems and applications. In recent years WACV has received an increasing number of algorithms papers without an applications focus. To maintain the WACV tradition of applications papers while accommodating algorithms papers, we created two separate reviewing criteria, and assigned Area Chairs to one or the other. We received approximately equal numbers of submissions in the two tracks, and reviewers generally adhered to the guidelines for each category resulting in high-‐quality accepted papers in each.

Also new to 2016 is an oral session format with two parallel tracks. Two oral sessions will run in parallel, each with about 15 5-‐minute talks. This format allows the sessions to be shorter than in previous years, in response to concerns that longer sessions of short talks were too demanding.

We received 442 original unpublished submissions to the main conference in a two round submission/review process, an increase of 17 papers from 2015. Out of these, 190 (85 in Round 1, 105 in Round 2) papers were accepted, resulting in an acceptance rate of 42.3%.

We used the CMT conference management service provided by Microsoft Research to manage the submission and selection of papers from the beginning to the end. To select papers from these submissions, we invited 43 researchers to act as Area Chairs (ACs). We recruited 378 experienced reviewers from the broader computer vision community.

WACV 2016 continued the two-‐round review process from 2014 and 2015 to provide the authors with an additional chance of defending and revising their papers, to make the best use of reviewers’ time, and to achieve an overall quality and consistency among the accepted papers. For Round 1, the decisions were accept, revise and resubmit, or reject. For Round 2, authors were invited to submit either a new, previously un-‐submitted paper -‐or-‐ resubmit a paper that was submitted in Round 1 and received a decision of “revise and resubmit”.

We strongly encouraged the authors of resubmitted papers (only “revise and resubmit” category from Round 1 to prepare a ‘rebuttal and list of changes’ in response to the reviewers’ comments in the first round. In the submission process, authors were asked if the paper was a resubmission, which was verified in the CMT system. For the resubmitted papers, we assigned the same reviewers and ACs as from the first round whenever possible.

After the submission deadlines, for both Round 1 and Round 2, the Program Chairs (PCs) assigned the papers to the reviewers and ACs. Almost all the papers were reviewed by a minimum of three reviewers. Once the reviews were returned, ACs made the initial decision about the paper selection. In a few cases the PCs discussed papers with the ACs to arrive at a final decision. The revise and resubmit process allowed by the two stage process served as a better proxy for the rebuttal process. Authors who submitted in Round 1 received this opportunity. The PCs did not submit papers to ensure there was absolutely no conflict of interest regarding any submission. As a GC with full access to CMT, Dr. Hoogs did not submit any papers. As allowed by PAMI TC policy, Dr. Davis chose not to be involved with reviewing decisions and was allowed to submit papers..Additionally, the ACs were excluded from any decisions associated with papers from their research groups, affiliated institutions or collaborators.

The main conference includes three invited speakers: Prof. Charles Stewart from Rensselaer Polytechnic Institute; Dr. Terry Adams, a computer vision program

Message from the General and Program Chairs

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manager from the Intelligence Advanced Research Projects Agency (IARPA), and Prof. Serge Belongie from Cornell Tech.

The proceedings of WACV 2016 are only being provided online before, during, and after the conference to all registered attendees. Unlike previous years, there will not be a USB proceedings, so attendees are encouraged to download the proceedings before the conference. All papers in the main conference and associated workshops will be made available through the IEEE Computer Society Digital Library and through IEEE Xplore.

We wish to thank all members of the Organizing Committee, the Area Chairs, reviewers, authors, and the CMT for the immense amount of hard work and

professionalism that have gone into making WACV 2016 a first-‐rate conference on the applications of computer vision. Our thanks also go to the organizers of WACV 2015 and the steering committee for their helpful advice and support. We are also grateful to the sponsors for their generous support.

Finally, we wish all the attendees a highly stimulating, informative, and enjoyable conference.

Anthony Hoogs, Larry Davis (General Co-‐Chairs)

Greg Mori, Robert Pless, Scott McCloskey, Rahul Sukthankar (Program Co-‐Chairs)

WACV 2016 Organizing Committee

General Chairs: Anthony Hoogs Larry Davis Program Chairs: Greg Mori Robert Pless Scott McCloskey Rahul Sukthankar

Workshops/Tutorials Chair: Matt Turek Publicity Chair: Matt Turek Publications Chair: Eric Mortensen Finance: Terrance Boult Local Arrangments Chair: Arslan Basharat

WACV 2016 Area Chairs

Zeynep Akata Jose M. Alvarez Lamberto Ballan Boulbaba Ben Amor Peter Carr David Crandall Shiloh Dockstader Sergio Escalera Bin Fan

Guoliang Fan Raghuraman Gopalan Riad Hammoud Timothy Hospedales Changbo Hu Mark Keck Adriana Kovashka Sebastian Kurtek Yi Li

Jongwoo Lim Jingen Liu Si Liu Xiaoming Liu Liliana Lo Presti Jiwen Lu Vijay Mahadevan Xue Mei Vinay P. Namboodiri

Vishal Patel Bogdan Raducanu Olga Russakovsky Michael S. Ryoo Mohammad Saberian Conrad Sanderson Vinay Sharma Yi-‐Zhe Song Yu-‐Wing Tai

Massimo Tistarelli Peter Tu Oncel Tuzel Guanghui Wang Hongcheng Wang Jan Dirk Wegner Ming-‐Hsuan Yang Zhaozheng Yin

1900–2100 Registration (Library) 1900–2100 Reception (Great Room)

Organizing Committee & Area Chairs

Sunday, March 6 Program

Monday, March 7 Program

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Monday, March 7

0730–0830 Registration (Library)

0730–0830 Breakfast (Olympic)


1430–1450 Coffee Break (Olympic)

1450–1500 Welcome by the General Chairs (Grandview & Sky)

1500–1615 Oral 1A: People / Faces (Grandview) Chair: Adriana Kovashka (Univ. of Pittsburgh)

Format (5 min. short presentation) 1. Optimal Feature Learning and Discriminative Framework

for Polarimetric Thermal to Visible Face Recognition, Benjamin S. Riggan, Nathaniel J. Short, Shuowen Hu

2. Discovery of Facial Motions Using Deep Machine Perception, Afsaneh Ghasemi, Simon Denman, Sridha Sridharan, Clinton Fookes

3. Customized Expression Recognition for Performance-‐Driven Cutout Character Animation, Xiang Yu, Jianchao Yang, Linjie Luo, Wilmot Li, Jonathan Brandt, Dimitris N. Metaxas

4. Going Deeper in Facial Expression Recognition Using Deep Neural Networks, Ali Mollahosseini, David Chan, Mohammad H. Mahoor

5. Discriminative FaceTopics for Face Recognition via Latent Dirichlet Allocation, Tejas Indulal Dhamecha, Praneet Sharma, Richa Singh, Mayank Vatsa

6. Can We Still Avoid Automatic Face Detection?, Michael J. Wilber, Vitaly Shmatikov, Serge Belongie

7. OpenFace: An Open Source Facial Behavior Analysis Toolkit, Tadas Baltrušaitis, Peter Robinson, Louis-‐Phillppe Morency

8. Correlation Filter Cascade for Facial Landmark Localization, Hamed Kiani Galoogahi, Terence Sim

9. Face Recognition Using Deep Multi-‐Pose Representations, Wael AbdAlmageed, Yue Wu, Stephen Rawls, Shai Harel, Tal Hassner, Iacopo Masi, Jongmoo Choi, Jatuporn Lekust, Jungyeon Kim, Prem Natarajan, Ram Nevatia, Gerard Medioni

10. Effect of Illicit Drug Abuse on Face Recognition, Daksha Yadav, Naman Kohli, Prateekshit Pandey, Richa Singh, Mayank Vatsa, Afzel Noore

11. Unconstrained Face Verification Using Deep CNN Features, Jun-‐Cheng Chen, Vishal M. Patel, Rama Chellappa

12. Frontal to Profile Face Verification in the Wild, Soumyadip Sengupta, Jun-‐Cheng Chen, Carlos Castillo, Vishal M. Patel, Rama Chellappa, David W. Jacobs

13. Capturing Facial Videos With Kinect 2.0: A Multithreaded Open Source Tool and Database, Daniel Merget, Tobias Eckl, Martin Schwörer, Philipp Tiefenbacher, Gerhard Rigoll

14. Naming TV Characters by Watching and Analyzing Dialogs, Monica-‐Laura Haurilet, Makarand Tapaswi, Ziad Al-‐Halah, Rainer Stiefelhagen

15. Direct Face Detection and Video Reconstruction From Event Cameras, Yoshitaka Miyatani, Souptik Barua, Ashok Veeraraghavan

1500–1615 Oral 1B: Detection / Tracking (Sky) Chair: Arslan Basharat (Kitware)

Format (5 min. short presentation) 1. Object Detection in 20 Questions, Xi Chen, He He, Larry S.

Davis 2. Pose Tracking by Efficiently Exploiting Global Features,

Ratnesh Kumar, Dhruv Batra 3. Exploring Bounding Box Context for Multi-‐Object Tracker

Fusion, Stefan Breuers, Shishan Yang, Markus Mathias, Bastian Leibe

4. OCPAD -‐ Occluded Checkerboard Pattern Detector, Peter Fürsattel, Sergiu Dotenco, Simon Placht, Michael Balda, Andreas Maier, Christian Riess

5. Leveraging Single for Multi-‐Target Tracking Using a Novel Trajectory Overlap Affinity Measure, Santiago Manen, Radu Timofte, Dengxin Dai, Luc Van Gool


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6. Procrustean Decomposition for Orthogonal Cascade Detection, Kun Duan, Wei Wang, Ting Yu

7. Region Graph Based Method for Multi-‐Object Detection and Tracking Using Depth Cameras, Sachin Mehta, Balakrishnan Prabhakaran

8. Online Tracking Using Saliency, Mohammed A. Yousefhussien, N. Andrew Browning, Christopher Kanan

9. Visual Tracking Using Anchor Templates, Luka Čehovin, Aleš Leonardis, Matej Kristan

10. A Structured Approach to Predicting Image Enhancement Parameters, Parag Shridhar Chandakkar, Baoxin Li

11. Active Contours for Selective Object Segmentation, Jozsef Molnar, Adam Istvan Szucs, Csaba Molnar, Peter Horvath

12. A Survey on Moving Object Detection for Wide Area Motion Imagery, Lars Wilko Sommer, Michael Teutsch, Tobias Schuchert, Jürgen Beyerer

13. Dynamic Belief Fusion for Object Detection, Hyungtae Lee, Heesung Kwon, Ryan M. Robinson, William D. Nothwang, Amar M. Marathe

14. Text Detection in Stores Using a Repetition Prior, Bo Xiong, Kristen Grauman

15. Cutting Through the Clutter: Task-‐Relevant Features for Image Matching, Rohit Girdhar, David F. Fouhey, Kris M. Kitani, Abhinav Gupta, Martial Hebert

1615–1715 Invited Talk (Grandview) • Charles Stewart (Rensselaer Polytechnic Institute)

Abstract: The Image-‐Based Ecological Information System (IBEIS) project is a collaboration of teams from Princeton Univ., RPI, Univ. Illinois-‐Chicago, and the non-‐profit WildMe. The goal of IBEIS is to ingest thousands of photos each day taken by field scientists, scouts, tourists, incidental photographers, camera traps, and vehicle-‐mounted cameras, and then detect the animals, determine their species, and, wherever possible, identify the individual animals. Various computer vision algorithms, both novel and adapted from existing work, have been applied to each step of this pipeline. Redundancy in the image collection and storage is important for improving algorithm effectiveness. Humans currently make all final decisions based on the results at each stage of the IBEIS computation, but more algorithm autonomy will be required as the system is scaled. The

Wildbook information management system is being fully integrated into IBEIS to store and manage all ecological data, including non-‐image metadata. IBEIS has been used for large-‐scale citizen science events to count the plains zebras and Masai giraffes in Nairobi National Park and to provide a census of the endangered Grevy’s zebra throughout Kenya. It is in daily use at the Lewa Wildlife Conservancy. We are working to extend IBEIS to monitor the population and study the migration of humpback whales and sea turtles. We plan to apply IBEIS to large carnivores in east Africa and in southern and central Asia.


1730–1855 Oral 1C: Faces / Actions (Grandview) Chair: Vijay Mahadevan (Yahoo Labs)

Format (5 min. short presentation) 1. A Multi-‐Modal Feature Fusion Framework for Kinect-‐

Based Facial Expression Recognition Using Dual Kernel Discriminant Analysis (DKDA), Sherin Aly, A. Lynn Abbott, Marwan Torki

2. Learning Patch-‐Dependent Kernel Forest for Person Re-‐Identification, Wei Wang, Ali Taalimi, Kun Duan, Rui Guo, Hairong Qi

3. Hide and Seek: Uncovering Facial Occlusion With Variable-‐Threshold Robust PCA, Wee Kheng Leow, Guodong Li, Jian Lai, Terence Sim, Vaishali Sharma

4. Score Reliability Based Weighting Technique for Score-‐Level Fusion in Multi-‐Biometric Systems, Waziha Kabir, M.Omair Ahmad, M.N.S. Swamy

5. HeHOP: Highly Efficient Head Orientation and Position Estimation, Anke Schwarz, Zhuang Lin, Rainer Stiefelhagen

6. A Revisit to Human Action Recognition From Depth Sequences: Guided SVM-‐Sampling for Joint Selection, Michel Antunes, Djamila Aouada, Björn Ottersten

7. Abstraction Hierarchy and Self Annotation Update for Fine Grained Activity Recognition, Song Cao, Kan Chen, Ram Nevatia

8. Activity Recognition and Prediction With Pose Based Discriminative Patch Model, Song Cao, Kan Chen, Ram Nevatia


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9. Deep Tree-‐Structured Face: A Unified Representation for Multi-‐Task Facial Biometrics, Rui Guo, Liu Liu, Wei Wang, Ali Taalimi, Chi Zhang, Hairong Qi

10. Recognition of Ongoing Complex Activities by Sequence Prediction Over a Hierarchical Label Space, Wenbin Li, Mario Fritz

11. Linear-‐Time Online Action Detection From 3D Skeletal Data Using Bags of Gesturelets, Moustafa Meshry, Mohamed E. Hussein, Marwan Torki

12. Efficient Video-‐Based Retrieval of Human Motion With Flexible Alignment, Ankur Gupta, John He, Julieta Martinez, James J. Little, Robert J. Woodham

13. Combining Multiple Sources of Knowledge in Deep CNNs for Action Recognition, Eunbyung Park, Xufeng Han, Tamara L. Berg, Alexander C. Berg

14. Person Re-‐Identification Using Deformable Patch Metric Learning, Slawomir Bak, Peter Carr

15. Support Vector Machines With Time Series Distance Kernels for Action Classification, Mohammad Ali Bagheri, Qigang Gao, Sergio Escalera

16. Face Fiducial Detection by Consensus of Exemplars, Mallikarjun B R, Visesh Chari, C. V. Jawahar, Akshay Asthana

17. One-‐to-‐Many Face Recognition With Bilinear CNNs, Aruni RoyChowdhury, Tsung-‐Yu Lin, Subhranshu Maji, Erik Learned-‐Miller

1730–1855 Oral 1D: Industrial / Medical / Traffic (Sky)

Chair: Faisal Qureshi (Univ. of Ontario Institute of Technology)

Format (5 min. short presentation) 1. Tooth Guard: A Vision System for Detecting Missing Tooth

in Rope Mine Shovel, Ser Nam Lim, Joao Soares, Ning Zhou 2. Multiscale Fully Convolutional Network With Application

to Industrial Inspection, Xiao Bian, Ser Nam Lim, Ning Zhou 3. Measuring and Modeling Apple Trees Using Time-‐of-‐Flight

Data for Automation of Dormant Pruning Applications, Somrita Chattopadhyay, Shayan A. Akbar, Noha M. Elfiky, Henry Medeiros, Avinash Kak

4. Texture Classification for Rail Surface Condition Evaluation, Ke Ma, Tomás F. Yago Vicente, Dimitris Samaras, Mike Petrucci, Daniel L. Magnus

5. Visual Recognition of Paper Analytical Device Images for Detection of Falsified Pharmaceuticals, Sandipan Banerjee, James Sweet, Christopher Sweet, Marya Lieberman

6. Deep Learning Architectures For Domain Adaptation in HOV/HOT Lane Enforcement, Safwan Wshah, Beilei Xu, Orhan Bulan, Jayant Kumar, Peter Paul

7. Learning Deep-‐Sea Substrate Types With Visual Topic Models, Arnold Kalmbach, Maia Hoeberechts, Alexandra Branzan Albu, Hervé Glotin, Sébastien Paris, Yogesh Girdhar

8. Detection of Cracks in Nuclear Power Plant Using Spatial-‐Temporal Grouping of Local Patches, Stephen J. Schmugge, Lance Rice, N. Rich Nguyen, John Lindberg, Robert Grizzi, Chris Joffe, Min C. Shin

9. An Elastic Functional Data Analysis Framework for Preoperative Evaluation of Patients With Rheumatoid Arthritis, Chafik Samir, Sebastian Kurtek, Anuj Srivastava, Noé Borges

10. A Deep Convolutional Neural Network Trained on Representative Samples for Circulating Tumor Cell Detection, Yunxiang Mao, Zhaozheng Yin, Joseph Schober

11. A New Computer Vision-‐Based System to Help Clinicians Objectively Assess Visual Pursuit With the Moving Mirror Stimulus for the Diagnosis of Minimally Conscious State, Thomas Hoyoux, Sarah Wannez, Thomas Langohr, Jérôme Wertz, Steven Laureys, Jacques G. Verly

12. Weighted Atlas Auto-‐Context With Application to Multiple Organ Segmentation, Telmo Amaral, Ilias Kyriazakis, Stephen J. McKenna, Thomas Plötz

13. Accurate 3D Bone Segmentation in Challenging CT Images: Bottom-‐Up Parsing and Contextualized Optimization, Le Lu, Dijia Wu, Nathan Lay, David Liu, Isabella Nogues, Ronald M. Summers

14. Real-‐Time Road Traffic Density Estimation Using Block Variance, Kratika Garg, Siew Kei Lam, Thambipillai Srikanthan, Vedika Agarwal

15. Monocular Obstacle Avoidance for Blind People Using Probabilistic Focus of Expansion Estimation, Sebastian Stabinger, Antonio Rodríguez-‐Sánchez, Justus Piater


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16. Atomic Scenes for Scalable Traffic Scene Recognition in Monocular Videos, Chao-‐Yeh Chen, Wongun Choi, Manmohan Chandraker

17. Eye-‐CU: Sleep Pose Classification for Healthcare Using Multimodal Multiview Data, Carlos Torres, Victor Fragoso, Scott D. Hammond, Jeffrey C. Fried, Bangalore S. Manjunath

1855– Dinner (Olympic)

1930–2130 Exhibits (Olympic) • Kitware • Northeastern University

1930–2130 Poster Session 1 (Olympic) Posters for Oral Sessions 1A, 1B, 1C, and 1D.

Notes:

Tuesday, March 8 Program

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Tuesday, March 8




Tutorial: Deep Learning for Computer Vision – From Foundations to Implementation Organizers: Reza Borhani Jeremy Watt Aggelos Katsaggelos Time: 0900-‐1200 (Half Day — Morning) Location: Sky Description: Due to their wide applicability, Deep Learning tools have quickly become important for today’s researchers in computer vision, machine learning, robotics, and related fields. In the past several years, Deep Learning has been used to great effect in both academia and industry, producing state of the art results on a variety of challenging computer vision and speech recognition problems.

This tutorial provides a user-‐friendly introduction to the basic tools of Deep Learning, describes their many applications, discusses how they relate to more traditional ideas in machine learning and computer vision, and provides an introduction to the most useful techniques from numerical optimization crucial to their implementation. We will spend the one third of the tutorial describing applications of Deep Learning, as well as its close connection to classic subjects in machine learning. During another third of the course we describe feed-‐forward neural networks more formally and in the context of function approximation, where we can more easily compare and contrast their effectiveness with more traditional kernel methods. Finally, roughly one third of the

class is dedicated to accessibly explaining the cutting edge methods from numerical optimization used in practice to implement Deep Learning systems. This coverage includes an overview of essential concepts from nonlinear programming, stochastic gradient descent, backpropagation, greedy techniques, as well as regularization and momentum methods.



1500–1615 Oral 2A: Vision for X (Grandview) Chair: Jose Alvarez (NICTA)

Format (5 min. short presentation) 1. Fashion Apparel Detection: The Role of Deep

Convolutional Neural Network and Pose-‐Dependent Priors, Kota Hara, Vignesh Jagadeesh, Robinson Piramuthu

2. Fixation Prediction With a Combined Model of Bottom-‐Up Saliency and Vanishing Point, Mengyang Feng, Ali Borji, Huchuan Lu

3. Is Image Super-‐Resolution Helpful for Other Vision Tasks?, Dengxin Dai, Yujian Wang, Yuhua Chen, Luc Van Gool

4. Energy-‐Efficient ConvNets Through Approximate Computing, Bert Moons, Bert De Brabandere, Luc Van Gool, Marian Verhelst

5. Fine-‐Grained Sketch-‐Based Image Retrieval: The Role of Part-‐Aware Attributes, Ke Li, Kaiyue Pang, Yi-‐Zhe Song, Timothy Hospedales, Honggang Zhang, Yichuan Hu

6. Toward Correlating and Solving Abstract Tasks Using Convolutional Neural Networks, Kuan-‐Chuan Peng, Tsuhan Chen

7. Assessing Tracking Performance in Complex Scenarios Using Mean Time Between Failures, Peter Carr, Robert T. Collins

8. A Crowdsourced Approach to Student Engagement Recognition in e-‐Learning Environments, Aditya Kamath, Aradhya Biswas, Vineeth Balasubramanian


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9. Color Multi-‐Fusion Fisher Vector Feature for Fine Art Painting Categorization and Influence Analysis, Ajit Puthenputhussery, Qingfeng Liu, Chengjun Liu

10. Constructing Image Mosaics Using Focus Based Depth Analysis, Mohamed A. Helala, Faisal Z. Qureshi

11. Image Set Classification by Symmetric Positive Semi-‐Definite Matrices, Masoud Faraki, Mehrtash T. Harandi, Fatih Porikli

12. Precise Deterministic Change Detection for Smooth Surfaces, Simon Stent, Riccardo Gherardi, Björn Stenger, Roberto Cipolla

13. Unsupervised Saliency Estimation Based on Robust Hypotheses, Fei Xu, Min Xian, H.D. Cheng, Jianrui Ding, Yingtao Zhang

14. On the Importance of Normalisation Layers in Deep Learning With Piecewise Linear Activation Units, Zhibin Liao, Gustavo Carneiro

15. Deep Learning the Dynamic Appearance and Shape of Facial Action Units, Shashank Jaiswal, Michel Valstar

1500–1615 Oral 2B: 3D / Robotics / Segmentation (Sky)

Chair: Fatih Porikli (Australian National Univ.)

Format (5 min. short presentation) 1. IPDC: Iterative Part-‐Based Dense Correspondence

Between Point Clouds, Rongqi Qiu, Ulrich Neumann 2. Categorizing Cubes: Revisiting Pose Normalization,

Mohsen Hejrati, Deva Ramanan 3. Unsupervised Categorical Shape Reconstruction Through

Manifolds, Kent Fujiwara, Minoru Mori, Kunio Kashino 4. Mobile Phone and Cloud -‐ A Dream Team for 3D

Reconstruction, Alex Locher, Michal Perdoch, Hayko Riemenschneider, Luc Van Gool

5. Online Inspection of 3D Parts via a Locally Overlapping Hierarchical Camera Network, Tolga Birdal, Emrah Bala, Tolga Eren, Slobodan Ilic

6. Omnidirectional Image Capture on Mobile Devices for Fast Automatic Generation of 2.5D Indoor Maps, Giovanni Pintore, Valeria Garro, Fabio Ganovelli, Marco Agus, Enrico Gobbetti

7. Where Is That Pixel in the Oblique-‐View Video?, Yin Li, Teck Khim Ng

8. Mono Camera Multi-‐View Diminished Reality, Philipp Tiefenbacher, Michael Sirch, Gerhard Rigoll

9. Mosaicing Scenes With a Quadcopter, Meghshyam G. Prasad, Sharat Chandran, Michael S. Brown

10. High Accuracy Model-‐Based Object Pose Estimation for Autonomous Recharging Applications, Hanno Jaspers, Georg R. Mueller, Hans-‐Joachim Wuensche

11. CoRBS: Comprehensive RGB-‐D Benchmark for SLAM Using Kinect v2, Oliver Wasenmüller, Marcel Meyer, Didier Stricker

12. Sky Segmentation in the Wild: An Empirical Study, Radu P. Mihail, Scott Workman, Zach Bessinger, Nathan Jacobs

13. Semantic Segmentation of Modular Furniture, Tobias Pohlen, Ishrat Badami, Markus Mathias, Bastian Leibe

14. Simultaneous Semantic Segmentation of a Set of Partially Labeled Images, Qiongjie Tian, Baoxin Li

1615–1715 Invited Talk (Grandview) • Unconstrained Face, Terry Adams (IARPA Program

Manager)

• Abstract: The Intelligence Advanced Research Projects Activity (IARPA) invests in high-‐risk, high-‐payoff research to tackle some of the most difficult challenges of the agencies and disciplines in the Intelligence Community. The Janus Program funds research focused on unconstrained face recognition. Previously, face recognition research focused on identification in controlled settings such as mugshots, frontal viewpoints or where illumination, age and other physical attributes have little variation. Janus is seeking breakthroughs in computer vision, machine learning and other fields that may lead to significant advances in automatic detection and recognition of faces in natural settings. The goal goes beyond producing the next state-‐of-‐the-‐art in face recognition, but aspires to spark a deeper understanding of the underlying A.I. techniques behind face recognition.

This talk will give an overview of the IARPA Janus Program. It will touch on some of the techniques explored in the program including: geometric modeling, machine learning, and search and retrieval methods. Other areas of exploration include deep learning, hierarchical models and


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adversarial examples where face matching breaks down. A reference to other IARPA programs in computer vision will be made, as well as some broad categories for new research.


1730–1855 Oral 2C: Geometry / 3D (Grandview) Chair: Shiloh Dockstader (Exelis Inc.)

Format (5 min. short presentation) 1. Direct 3D Pose Estimation of a Planar Target, Hung-‐Yu

Tseng, Po-‐Chen Wu, Ming-‐Hsuan Yang, Shao-‐Yi Chien 2. Forget the Checkerboard: Practical Self-‐Calibration Using

a Planar Scene, Daniel Herrera Castro, Juho Kannala, Janne Heikkilä

3. 6DOF Point Cloud Alignment Using Geometric Algebra-‐Based Adaptive Filtering, Anas Al-‐Nuaimi, Wilder B. Lopes, Eckehard Steinbach, Cassio G. Lopes

4. Unifying Diffuse and Specular Reflections for the Photometric Stereo Problem, Roberto Mecca, Yvain Quéau

5. Underwater 3D Capture Using a Low-‐Cost Commercial Depth Camera, Sundara Tejaswi Digumarti, Aparna Taneja, Amber Thomas, Gaurav Chaurasia, Roland Siegwart, Paul Beardsley

6. Resolution Enhancement in Single Depth Map and Aligned Image, Yang Xian, Yingli Tian

7. Geometric Calibration for Mobile, Stereo, Autofocus Cameras, Stephen DiVerdi, Jonathan T. Barron

8. Lifting GIS Maps Into Strong Geometric Context for Scene Understanding, Raúl Díaz, Minhaeng Lee, Jochen Schubert, Charless C. Fowlkes

9. Heat Propagation Contours for 3D Non-‐Rigid Shape Analysis, Xupeng Wang, Ferdous Sohel, Mohammed Bennamoun, Hang Lei

10. Dealing With Small Data and Training Blind Spots in the Manhattan World, Muhammad Wajahat Hussain, Javier Civera, Luis Montano, Martial Hebert

11. Automatic 3D Reconstruction of Manifold Meshes via Delaunay Triangulation and Mesh Sweeping, Andrea Romanoni, Amaël Delaunoy, Marc Pollefeys, Matteo Matteucci

12. Half Hypersphere Confinement for Piecewise Linear Regression, Eduardo Pérez-‐Pellitero, Jordi Salvador, Javier Ruiz-‐Hidalgo, Bodo Rosenhahn

13. 3D Shape Retrieval Using a Single Depth Image From Low-‐Cost Sensors, Jie Feng, Yan Wang, Shih-‐Fu Chang

14. Architectural Decomposition for 3D Landmark Building Understanding, Nikolay Kobyshev, Hayko Riemenschneider, András Bódis-‐Szomorú, Luc Van Gool

15. Voting-‐Based 3D Object Cuboid Detection Robust to Partial Occlusion From RGB-‐D Images, Sangdoo Yun, Hawook Jeong, Soowan Kim, Jin Young Choi

16. Joint Object Recognition and Pose Estimation Using a Nonlinear View-‐Invariant Latent Generative Model, Amr Bakry, Tarek El-‐Gaaly, Mohamed Elhoseiny, Ahmed Elgammal

17. The Generalized Relative Pose and Scale Problem: View-‐Graph Fusion via 2D-‐2D Registration, Laurent Kneip, Chris Sweeney, Richard Hartley

1730–1855 Oral 2D: Aerial / Mobile (Sky) Chair: Nathan Jacobs (Univ. of Kentucky)

Format (5 min. short presentation) 1. Efficient Joint Stereo Estimation and Land Usage

Classification for Multiview Satellite Data, Ke Wang, Craig Stutts, Enrique Dunn, Jan-‐Michael Frahm

2. Automatic Detection and Analysis of Photovoltaic Modules in Aerial Infrared Imagery, Sergiu Dotenco, Manuel Dalsass, Ludwig Winkler, Tobias Würzner, Christoph Brabec, Andreas Maier, Florian Gallwitz

3. Open Source Structure-‐From-‐Motion for Aerial Video, Matthew J. Leotta, Eric Smith, Matthew Dawkins, Paul Tunison

4. Person-‐Following UAVs, Francisca Vasconcelos, Nuno Vasconcelos

5. Detection of Quadrilateral Document Regions From Digital Photographs, Jian Fan

6. An FPGA-‐Accelerated Partial Duplicate Image Retrieval Engine for a Document Search System, Hidetoshi Matsumura, Masahiko Sugimura, Hironobu Yamasaki, Yasumoto Tomita, Takayuki Baba, Yasuhiro Watanabe


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7. A Fast and Robust Text Spotter, Siyang Qin, Roberto Manduchi

8. Persistent 3D Stabilization for Aerial Imagery, Bor-‐Jeng Chen, Gérard Medioni

9. A Two-‐Stage Detector for Hand Detection in Ego-‐Centric Videos, Xiaolong Zhu, Wei Liu, Xuhui Jia, Kwan-‐Yee K. Wong

10. Real-‐Time Eye Pupil Localization Using Hough Regression Forest, Amine Kacete, Renaud Séguier, Jérôme Royan, Michel Collobert, Catherine Soladie

11. A Novel Inheritable Color Space With Application to Kinship Verification, Qingfeng Liu, Ajit Puthenputhussery, Chengjun Liu

12. A Real-‐Time Visual Card Reader for Mobile Devices, Lukas Stehr, Robert Meusel, Stephan Kopf

13. Accurate and Efficient Pulse Measurement From Facial Videos on Smartphones, Chong Huang, Xin Yang, Kwang-‐Ting Cheng

14. Discovering Useful Parts for Pose Estimation in Sparsely Annotated Datasets, Mikhail Breslav, Tyson L. Hedrick, Stan Sclaroff, Margrit Betke

15. Arrays of Single Pixel Time-‐Of-‐Flight Sensors for Privacy Preserving Tracking and Coarse Pose Estimation, Indrani Bhattacharya, Richard J. Radke

16. A Driver Fatigue Detection Method Based on Multi-‐Sensor Signals, Hao Yin, Yuanqi Su, Yuehu Liu, Danchen Zhao




Notes:

Wednesday, March 9 Program

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Wednesday, March 9




Tutorial: Domain Adaptation for Visual Recognition Organizers: Vishal M. Patel Raghuraman Gopalan Time: 0900-‐1200 (Half Day — Morning) Location: Sky Description: In pattern recognition and computer vision, one is often faced with scenarios where the training data used to learn a model has a different distribution from the data on which the model is applied. Regardless of the cause, any distributional change that occurs after learning a classifier can degrade its performance at test time. Domain adaptation tries to mitigate this degradation. In this tutorial, we will give an overview of recent visual domain adaptation methods and their applications in object recognition and biometrics recognition problems. We will also discuss adaptation in the context of big data with heterogeneous data modalities, and its relation with other learning problems.



1500–1615 Oral 3A: Biometrics / People (Grandview)

Chair: Riad Hammoud (BAE Systems)

Format (5 min. short presentation) 1. Accurate Eye Center Localization Using Snakuscule,

Sanyam Garg, Abhinav Tripathi, Edward Cutrell 2. Furthering Fingerprint-‐Based Authentication: Introducing

the True-‐Neighbor Template, Fawaz E. Alsaadi, Terrance E. Boult

3. A Practical Approach to Real-‐Time Neutral Feature Subtraction for Facial Expression Recognition, Nick Haber, Catalin Voss, Azar Fazel, Terry Winograd, Dennis P. Wall

4. Person Re-‐Identification Using Multiple First-‐Person-‐Views on Wearable Devices, Anirban Chakraborty, Bappaditya Mandal, Hamed Kiani Galoogahi

5. A Coarse-‐To-‐Fine Deep Learning for Person Re-‐Identification, Alexandre Franco, Luciano Oliveira

6. Analyzing Human Appearance as a Cue for Dating Images, Tawfiq Salem, Scott Workman, Menghua Zhai, Nathan Jacobs

7. Multimodal Emotion Recognition Using Deep Learning Architectures, Hiranmayi Ranganathan, Shayok Chakraborty, Sethuraman Panchanathan

8. Fine-‐Tuning Human Pose Estimations in Videos, Digvijay Singh, Vineeth Balasubramanian, C. V. Jawahar

9. An Enhanced Deep Feature Representation for Person Re-‐Identification, Shangxuan Wu, Ying-‐Cong Chen, Xiang Li, An-‐Cong Wu, Jin-‐Jie You, Wei-‐Shi Zheng

10. Crowd Density Estimation Based on Rich Features and Random Projection Forest, Bolei Xu, Guoping Qiu

11. People Detection in Crowded Scenes by Context-‐Driven Label Propagation, Jingjing Liu, Quanfu Fan, Sharath Pankanti, Dimitris N. Metaxas


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12. Efficient Unsupervised Abnormal Crowd Activity Detection Based on a Spatiotemporal Saliency Detector, Yilin Wang, Qiang Zhang, Baoxin Li

13. Vision-‐Based Counting of Pedestrians and Cyclists, Mehmet Kemal Kocamaz, Jian Gong, Bernardo R. Pires

14. Static Action Recognition by Efficient Greedy Inference, Shaukat Abidi, Massimo Piccardi, Mary-‐Anne Williams

15. An Analysis of 1-‐to-‐First Matching in Iris Recognition, Andrey Kuehlkamp, Kevin W. Bowyer

1500–1615 Oral 3B: Learning (Sky) Chair: Yi Li (NICTA)

Format (5 min. short presentation) 1. Self-‐Taught Object Localization With Deep Networks,

Loris Bazzani, Alessandro Bergamo, Dragomir Anguelov, Lorenzo Torresani

2. Learning a Structured Dictionary for Video-‐Based Face Recognition, Hongyu Xu, Jingjing Zheng, Azadeh Alavi, Rama Chellappa

3. Kernel Auto-‐Encoder for Semi-‐Supervised Hashing, Behnam Gholami, Abolfazl Hajisami

4. Higher-‐Order Class-‐Specific Priors for Semantic Segmentation of 3D Outdoor Scenes, Bingxiao Tang, Yu Zhou, Yao Yu, Sidan Du

5. Multi-‐View Dynamic Texture Learning, Thanh Minh Nguyen, Q. M. Jonathan Wu

6. Automatic and Quantitative Evaluation of Attribute Discovery Methods, Liangchen Liu, Arnold Wiliem, Shaokang Chen, Brian C. Lovell

7. Deep Recursive and Hierarchical Conditional Random Fields for Human Action Recognition, Tianliang Liu, Xincheng Wang, Xiubin Dai, Jiebo Luo

8. A New Image Transformatiom Method Using Linear Discriminant Analysis (LDA) and Kernel Mapping (k-‐vector), Sepehr Damavandinejadmonfared, Vijay Varadharajan

9. Think Big, Solve Small: Scaling Up Robust PCA With Coupled Dictionaries, Jian Lai, Wee Kheng Leow, Terence Sim, Vaishali Sharma

10. Discriminative Training of CRF Models With Probably Submodular Constraints, Wojciech Zaremba, Matthew B. Blaschko

11. Efficient Transductive Semantic Segmentation, Jose M. Alvarez, Mathieu Salzmann, Nick Barnes

12. Unsupervised Network Pretraining via Encoding Human Design, Ming-‐Yu Liu, Arun Mallya, Oncel Tuzel, Xi Chen

13. Coupled Depth Learning, Mohammad Haris Baig, Lorenzo Torresani

14. Fine-‐Grained Classification via Mixture of Deep Convolutional Neural Networks, Zong Yuan Ge, Alex Bewley, Christopher McCool, Peter Corke, Ben Upcroft, Conrad Sanderson

15. An End-‐To-‐End Generative Framework for Video Segmentation and Recognition, Hilde Kuehne, Juergen Gall, Thomas Serre

1615–1715 Invited Talk (Grandview) • Fine Grained Visual Category Recognition and Perceptual

Embedding, Serge Belongie (Cornell Tech)

Abstract: In this talk I will provide an overview of my group's research projects at Cornell Tech involving Computer Vision, Machine Learning and Human in the Loop Computing. Specific examples of projects we will cover include bird identification and learning perceptual embeddings of food.


1730–1855 Oral 3C: Video / Actions / Scenes (Grandview)

Chair: Matt Turek (Kitware)

Format (5 min. short presentation) 1. Detecting Temporally Consistent Objects in Videos

Through Objects Class Label Propagation, Subarna Tripathi, Serge Belongie, Youngbae Hwang, truong Nguyen

2. A Mid-‐Level Representation of Visual Structures for Video Compression, Georgios Georgiadis, Stefano Soatto

3. Video Summarization for Remote Invigilation of Online Exams, Melissa Cote, Frédéric Jean, Alexandra Branzan Albu, David Capson


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4. Automatic Video Editing for Sensor-‐Rich Videos, Wesley Taylor, Faisal Z. Qureshi

5. Tag-‐Based Video Retrieval by Embedding Semantic Content in a Continuous Word Space, Arnav Agharwal, Rama Kovvuri, Ram Nevatia, Cees G.M. Snoek

6. Discovering Picturesque Highlights From Egocentric Vacation Videos, Vinay Bettadapura, Daniel Castro Chin, Irfan Essa

7. Compact CNN for Indexing Egocentric Videos, Yair Poleg, Ariel Ephrat, Shmuel Peleg, Chetan Arora

8. Transition Hough Forest for Trajectory-‐Based Action Recognition, Guillermo Garcia-‐Hernando, Hyung Jin Chang, Ismael Serrano, Oscar Deniz, Tae-‐Kyun Kim

9. Is Alice Chasing or Being Chased? : Determining Subject and Object of Activities in Videos, Teng Zhang, Liangchen Liu, Arnold Wiliem, Brian Lovell

10. High Performance Moves Recognition and Sequence Segmentation Based on Key Poses Filtering, Cláudio Márcio De Souza Vicente, Erickson R. Nascimento, Luiz Eduardo C. Emery, Cristiano Arruda G. Flor, Thales Vieira, Leonardo B. Oliveira

11. The Geometry of a Scene: On Deep Semantics for Visual Perception Driven Cognitive Film Studies, Jakob Suchan, Mehul Bhatt

12. A Fast Method for Estimating Transient Scene Attributes, Ryan Baltenberger, Menghua Zhai, Connor Greenwell, Scott Workman, Nathan Jacobs

13. MIDI-‐Assisted Egocentric Optical Music Recognition, Liang Chen, Kun Duan

14. The ULg Multimodality Drowsiness Database (Called DROZY) and Examples of Use, Quentin Massoz, Thomas Langohr, Clémentine François, Jacques G. Verly

15. Task-‐Driven Progressive Part Localization for Fine-‐Grained Recognition, Chen Huang, Zhihai He

16. KrishnaCam: Using a Longitudinal, Single-‐Person, Egocentric Dataset for Scene Understanding Tasks, Krishna Kumar Singh, Kayvon Fatahalian, Alexei A. Efros

17. Generating Reliable Video Annotations by Exploiting the Crowd, Roberto Di Salvo, Concetto Spampinato, Daniela Giordano

1730–1855 Oral 3D: Features / Registration / Shape (Sky)

Chair: Schmuel Peleg (The Hebrew Univ. of Jerusalem)

Format (5 min. short presentation) 1. Extended Coherent Point Drift Algorithm With

Correspondence Priors and Optimal Subsampling, Vladislav Golyanik, Bertram Taetz, Gerd Reis, Didier Stricker

2. Occlusion-‐Aware Video Registration for Highly Non-‐Rigid Objects, Bertram Taetz, Gabriele Bleser, Vladislav Golyanik, Didier Stricker

3. Optimal Radiometric Calibration for Camera-‐Display Communication, Eric Wengrowski, Wenjia Yuan, Kristin J. Dana, Ashwin Ashok, Marco Gruteser, Narayan Mandayam

4. Decomposing Time Series With Application to Temporal Segmentation, Jiaping Zhao, Laurent Itti

5. LATCH: Learned Arrangements of Three Patch Codes, Gil Levi, Tal Hassner

6. Texture Instance Similarity via Dense Correspondences, Tal Hassner, Gilad Saban, Lior Wolf

7. Mode-‐Shape Interpretation: Re-‐Thinking Modal Space for Recovering Deformable Shapes, Antonio Agudo, J.M.M. Montiel, Begoña Calvo, Francesc Moreno-‐Noguer

8. Line Segment Matching: A Benchmark, Kai Li, Jian Yao, Mengsheng Lu, Yuan Heng, Teng Wu, Yinxuan Li

9. Binary Patterns for Shape Description in RGB-‐D Object Registration, Cristina Romero-‐González, Jesus Martínez-‐Gómez, Ismael García-‐Varea, Luis Rodríguez-‐Ruiz

10. Joint Geometric Graph Embedding for Partial Shape Matching in Images, Anirban Mukhopadhyay, Arun CS Kumar, Suchendra M. Bhandarkar

11. Variational Multi-‐Phase Segmentation Using High-‐Dimensional Local Features, Niklas Mevenkamp, Benjamin Berkels

12. Graph Matching With Low-‐Rank Regularization, Tianshu Yu, Ruisheng Wang

13. Adapting Attributes by Selecting Features Similar Across Domains, Siqi Liu, Adriana Kovashka

14. Predicting Wide Receiver Trajectories in American Football, Namhoon Lee, Kris M. Kitani


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15. Human and Sheep Facial Landmarks Localisation by Triplet Interpolated Features, Heng Yang, Renqiao Zhang, Peter Robinson

16. Joint Point and Line Segment Matching on Wide-‐Baseline Stereo Images, Kai Li, Jian Yao, Menghan Xia, Li Li

17. A Two-‐Sample Test for Statistical Comparisons of Shape Populations, Wade Henning, Anuj Srivastava




Notes:

Thursday, March 10 Workshops

15

Thursday, March 10


0730–0830 Breakfast (Olympic 1)

1015–1045 Coffee Break (Olympic 1)

1200–1300 Lunch (Olympic 1)


1515–1545 Coffee Break (Olympic 1)

Computer Vision in Healthcare Organizers: Alejandro (Alex) Jaimes Location: Olympic 2 Schedule: Half Day (Morning) 0900 Invited Talk: TBA

0945 Short Presentations (by authors)

1015 Morning Break

1030 Group Discussions

1130 Group Presentations

1200 Summary & Closing Remarks

Computer Vision Applications in Surveillance and Transportation Organizers: Orhan Bulan Robert Loce Yang Cai Location: Olympic 3 Schedule: Full Day 0900 Opening Remarks

0910 Invited Talk: Transportation Imaging Applications at PARC, Aaron Burry (PARC)

0950 Low Resolution Vehicle Re-‐Identification Based on Appearance Features for Wide Area Motion Imagery, Mickael Cormier, Lars Wilko Sommer, Michael Teutsch

1010 Scene-‐Independent Feature-‐ and Classifier-‐Based Vehicle Headlight and Shadow Removal in Video Sequences, Qun Li, Edgar A. Bernal, Matthew Shreve, Robert P. Loce

1030 Morning Break

1120 Superpixels Shape Analysis for Carried Object Detection, Blanca Delgado, Khalid Tahboub, Edward J. Delp

1140 Efficient Object Annotation for Surveillance and Automotive Applications, Sirnam Swetha, Anand Mishra, Guruprasad M. Hegde, C.V. Jawahar

1200 Lunch (Olympic 1)

1300 Invited Talk: Intersection Monitoring Using Computer Vision, Brendan Morris (Univ. of Nevada, Las Vegas)

1340 Filling in the Blanks: Reconstructing Microscopic Crowd Motion From Multiple Disparate Noisy Sensors, Sejong Yoon, Mubbasir Kapadia, Pritish Sahu, Vladimir Pavlovic

1400 Image Surveillance Assistant, Michael Maynord, Sambit Bhattacharya, David W. Aha

1420 Model-‐Less and Model-‐Based Computationally Efficient Motion Estimation for Video Compression in Transportation Applications, Edgar A. Bernal, Qun Li, Orhan Bulan, Wencheng Wu, Stuart Schweid

Thursday, March 10 Workshops

16

Automated Analysis of Video Data for Wildlife Surveillance Organizers: Benjamin Richards Anthony Hoogs David Kriegman Location: Sky Schedule: Full Day 0900 Overview of NOAA Fisheries Strategic Initiative on

Automated Image Analysis, Benjamin Richards

1000 Unsupervised Underwater Fish Detection Fusing Flow and Objectiveness, David Zhang, Giorgos Kopanas, Chaitanya Desai, Sek Chai, Michael Piacentino

1030 Morning Break

1045 Invited Talk: Kaggle Challenge: Identify Endangered Right Whales in Aerial Photographs, Christin Khan (NOAA Fisheries)

1145 TBA

1215 Lunch (Olympic 1)

1315 Invited Talk: CoralNet: A User Experience, Brett Schumacher (NOAA Fisheries)

1415 VIAME Open Source Framework for Underwater Image Processing, Anthony Hoogs

1445 Invited Talk: Development of a System to Automate Analysis of Fisheries Information from Digital Stills, Kevin Sullivan (New Hampshire Fish & Game Dept.)

1545 Afternoon Break

1600 Discussion: Moderator -‐ Benjamin Richards

Notes:

Documents

Message&from&the&General&and&Program&Chairs&wacv16.wacv.net/wp-content/uploads/2016/02/WACV... · Message&from&the&General&and&Program&Chairs& 1!! Welcome’to’Lake’Placid,’NY,’and’the’16th’edition’of’