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LoCaF : Detecting Real-World States with Lousy Wireless Cameras. Benjamin Meyer, Richard Mietz , Kay Römer. Structure. Introduction Motivation Challenges System Architecture Evaluation. Motivation. SFpark project: http://sfpark.org/. Towards the Internet of Things - PowerPoint PPT Presentation
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LoCaF:Detecting Real-World
States with Lousy Wireless Cameras
Benjamin Meyer, Richard Mietz, Kay Römer
1
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
2
Introduction– Motivation– Challenges
System Architecture Evaluation
Structure
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
3
Towards the Internet of Things– High-level state of things
on the internet– Scalar/specialized sensors
are often limited to one scenario
– Cameras are more flexible
Motivation
SFpark project:
http://sfpark.org/
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Sensor nodes– Constrained
resources Low-cost cameras
– Low resolution– Poor image quality– Low frame rate
Processing is shifted to the gateway
Low-cost hardware
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
5
ScenariosOccupancy of a
roomFree seats in a
roomIndividual
occupancy of parking spots
States Free/occupied Number of persons
Free/occupied for each parking spot
Challenges Possibly lots of movement
Possibly lots of movement
Outdoor Changing lighting
conditions
Picture
Objects to detect People People Cars
Flexible Framework to infer and publish states for divers scenarios
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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System Architecture: Overview
0
HTML
RDF
SQL
Tweet
Image capture Compression Wireless transmission
State publication Text templates Different media
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
Customizable workflow
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
7
0
HTML
RDF
SQL
Tweet
State publication Text templates Different media
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
System Architecture: Sensor Node
Image capture Compression Wireless transmission
Customizable workflow
Camera equipped sensor node
Two capture modes– Time-triggered– Event-triggered (by PIR)
JPEG-compression in hardware
Fragmented transmission to gateway
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
8
0
HTML
RDF
SQL
Tweet
State publication Text templates Different media
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
Image capture Compression Wireless transmission
Customizable workflow
Image processing
Regions of interest
Enhancing filters
System Architecture: Processing
INSTITUTE OF COMPUTER ENGINEERING
Parking spot a
Parking spot b
Region selection Lighting compensation Texture enhancement Contrast enhancement Orchestration and
parameterization of enhancements
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
9
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
Object detection
Face detection Mobile object
detection
Face detection Adaptive background
subtraction– Classification into fore- and
background– Can adapt to small changes
Blob detection– Each blob is an object
Number of & area covered by objects
System Architecture: Processing
INSTITUTE OF COMPUTER ENGINEERING
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
10
0
HTML
RDF
SQL
Tweet
State publication Text templates Different media
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
Image capture Compression Wireless transmission
State inference Rule-based
language
Customizable workflow
Rule-based state inferencecount:map:0:1:freecount:map:1:-1:occupied
State-based
Event-based
area:switch:free:80:occupiedarea:switch:occupied:80:free
System Architecture: Processing
INSTITUTE OF COMPUTER ENGINEERING
count:map:0:1:All seats freecount:map:10:45:Enough seatscount:map:45:70:Almost fullcount:map:70:-1:No seats left
count:map:0:1:freecount:map:1:-1:occupied
area:map:0:80:freearea:map:80:100:occupied
free
occupied
80% covera
ge
80% covera
ge
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
11
0
HTML
RDF
SQL
Tweet
State publication Text templates Different media
Image processing
Regions of interest
Enhancing filters
Object detection
Face detection Mobile object
detection
State inference Rule-based
language
System Architecture: Publishing
Image capture Compression Wireless transmission
Customizable workflow
Every text format (HTML, RDF, TXT, …) Template-based Publishing via
– FTP– Twitter– SQL-Database
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Camera in front of lecture hall during lecture
Estimate number of students Also looking at binary state
(free/occupied) One region, background subtraction &
no filter Three phases:
– Beginning: Entering persons in dribs and drabs
– During: Not many movements– End: Abrupt leaving of students
Evaluation Setup
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Evaluation: Under- and Overestimation Underestimation
– Several persons identified as one
– Persons not recognized because of no movement
Overestimation– Legs recognized as
individual
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
14
Evaluation: Entry phase
OE: 130%
UE: 70%
Avg: 48%Binary state always correct
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Evaluation: Lecture phase
UE: 105%
Avg: 54%Binary state always correct
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Evaluation: Exit phase
OE: ∞
UE: 222%
Avg: 95%Binary state not correct for picture 11-13
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
17
Evaluation: Entry phase revisited
Image filters can significantly change the estimation
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Evaluation: Entry phase revisited
Parameters can significantly change the estimation
Improved avg error: 12%
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Conclusion Flexible framework Use of cameras to be applicable in
divers scenarios Fully customizable by the user in each
step Accuracy quite high
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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Questions?
Thank you for your attention.
Time for questions.
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
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SetupCamera
node
Gateway Netbook with software
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
The Framework: Connection Configuration
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
The Framework: Data Exchange
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
The Framework: Image Processing
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
The Framework: Region Selection / State Inference
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
The Framework: Publishing
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
Filter
INSTITUTE OF COMPUTER ENGINEERING
Richard Mietz LoCaF: Detecting Real-World States with Lousy Cameras
28
Evaluation: Parking Spot Scenario
area:switch:free:80:occupiedarea:switch:occupied:80:free Select single spot State switches from free to occupied when car enters (b) and c))
State will switch back when car leaves