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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 731667 (MULTIDRONE) MULTIPLE DRONE CINEMATOGRAPHY I. Mademlis 1 , I. Pitas 1 , A. Messina 2 1 Aristotle University of Thessaloniki 2 Rai - Centre for Research and Technological Innovation

MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

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Page 1: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

MULTIPLE DRONE CINEMATOGRAPHYI. Mademlis1, I. Pitas1, A. Messina2

1 Aristotle University of Thessaloniki2 Rai - Centre for Research and Technological Innovation

Page 2: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Page 3: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• H2020 ICT-26 2016

• Research and Innovation Actions on multiple-actor

systems

• 8 partners

• Univ. of Thessaloniki, University of Bristol, THALES, RAI,

Deutsche Welle, Istituto Superior Tecnico, Univ. of

Seville, Alerion

• 2017-2020

MULTIDRONE in a nutshell

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Improved multiple drone decisional autonomy, robustness and safety;

• Innovative, safe and fast multiple drone active perception and AV shooting

• Application and demonstration in three media production scenarios

Main Objectives

Page 5: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• UAV cinematography is mainly derived from traditional

ground and aerial cinematography, but must also take

into account UAV-specific limitations, capabilities,

properties.

• A visual vocabulary of UAV cinematography can be

defined, consisting in:

• Shot types

• Combinations of framing shot types + UAV / camera

motion types.

© 2009, Jim Zuckerman

UAV Cinematography

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Composition principles:

• Central Composition.

• Rule of Thirds.

• Lighting rules.

• Depth-of-Field / Focus settings.

• Need to define a standardized UAV shot type taxonomy

UAV Cinematography

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Actual drone footage and related articles / guidelines were used to this

end:

• A total of 8 framing (static) shot types and 26 UAV / camera motion types

suitable for UAV media production have been identified.

• Camera motion types were clustered into groups according to their

characteristics.

• Visually pleasing combinations of framing shot types and camera motion types

were identified.

UAV Cinematography

Page 8: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Framing Shot Types are more or less those of traditional

cinematography.

• Most are defined based on the percentage of the video frame width /

height covered by the single target / subject.

FRAMING SHOT TYPEPercentage of frame width/height

covered by target

Extreme Long Shot (ELS) <5%

Very Long Shot (VLS) 5-20%

Long Shot (LS) 20-40%

Medium Shot (MS) 40-60%

Medium Close Up (MCU) 60-75%

Close Up (CU) >75%

Framing Shot Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• A couple of Framing Shot Types deal with two or more

subjects / targets:

• 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible

(typically LS or MS).

• Over the Shoulder (OTS): Adapted from traditional

cinematography OTS. Main target fully visible, secondary target

visible at the video frame edge.

Framing Shot Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Example UAV shot types when shooting boat targets from the side.

Extreme Long Shot Long Shot

Medium Close Up Two Shot

Framing Shot Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• UAV / camera motion types can be considered as either

“scene-oriented” or “target-oriented”.

• Four groups of UAV / camera motion types were defined.

• Static shots (6). No UAV motion, target may or may not be

present:

• Static Shot (SS)

• Static Shot of Still Target (SSST)

• Static Shot of Moving Target (SSMT)

• Static Aerial Pan (SAP)

• Static Aerial Tilt (SAT).

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Dynamic shots (6). Moving UAV, no target:

• Moving Aerial Pan or Tilt (MAP, MAT)

• Pedestal / Elevator Shot (PS)

• Bird’s Eye Shot (BIRD)

• Moving Bird’s Eye Shot (MOVBIRD)

• Survey Shot (SURVEY)

• Fly-Through (FLYTHROUGH).

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Target Tracking shots (11). UAV motion depends on target

motion:

• Moving Aerial Pan with Moving Target (MAPMT)

• Moving Aerial Tilt with Moving Target (MATMT)

• Lateral Tracking Shot (LTS)

• Vertical Tracking Shot (VTS)

• Orbit (ORBIT)

• Fly-Over (FLYOVER)

• Fly-By (FLYBY).

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Target Tracking shots (continued)

• Chase/Follow Shot (CHASE)

• Descent (DESCENT)

• Descent-Over (DESCENTOVER)

• Ascent (ASCENT)

UAV / Camera Motion Types

Page 15: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Source: Youtube: "5 Drone Moves Every Flier

Should Know",

https://www.youtube.com/watch?v=1hz-

lkx4o6c

Lateral Tracking Shot (LTS)

• Camera stays focused on the

moving target.

• UAV flies sideways / in parallel to

the target, matching its speed.

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Source: Youtube: "Drone footage of Cycle-

Racing",

https://www.youtube.com/watch?v=vQ94R

4LC9ig

Chase/Follow (CHASE)

• Camera stays focused on the

moving target.

• UAV follows / leads the target

from behind / from the front,

matching its speed.

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Source: Youtube: "Drone Chasing

Horses",

https://www.youtube.com/watch?v=O0

uw8py9qmw

Orbit (ORBIT)

• Camera gimbal is slowly rotating,

so as to keep the still or moving

target properly framed.

• UAV circles around the target while

following its trajectory (if any).

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

UAV / Camera Motion Types

Static Aerial Tilt (SAT)

• UAV hovers.

• Camera gimbal rotates slowly

around the pitch axis in order to

capture the scene context.

Source: Youtube: "5 Drone Moves

Every Flier Should Know",

https://www.youtube.com/watch?v

=1hz-lkx4o6c

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

UAV / Camera Motion Types

Source: Youtube: "How to

film amazing aerials with

your drone |

DroneFilmSchool",

https://www.youtube.com/wat

ch?v=zmQcSdj7vbE

Moving Bird’s Eye Shot

(MOVBIRD)

• Camera remains stable facing

vertically down.

• UAV is slowly flying parallel to

the terrain with constant velocity.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

UAV / Camera Motion Types

Source: Youtube: "Manor

House Stables - Drone Film -

Horses",

https://www.youtube.com/wat

ch?v=56qOnxc28dw

copyright owner: M7 Aerial

Survey Shot

• Camera remains stable facing

ahead or backwards.

• UAV is slowly flying parallel to

the terrain with constant velocity.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Dynamic Target shots (3): a target exists, but UAV trajectory also depends on

other factors

• Constrained Lateral Tracking Shot (CONLTS)

• Pedestal/Elevator with Target (PST)

• Reveal Shot (REVEAL)Constrained Lateral Tracking Shot

(CONLTS)

• Camera remains stable, focused on the

moving target.

• UAV follows the target but it is

constrained to move onto a pre-defined

“flight plane” vertical to the ground plane.

• Useful in sports, e.g. football.

UAV / Camera Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

• Motion types involving 2 or more drones in orchestrated

motion can be also considered.

Multiple UAV Motion Types

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Target detection

Page 24: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Target detection

Page 25: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Target detection• Target/object examples: athletes, boats, biclycles.

Page 26: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Target detection

Page 27: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection

• Single view object detection

• Deep learning (CNN) object detection.

• Light weight CNNs for object detection.

• Multiple view object detection.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection

• Object detection = classification + localization:

• Find what is in a picture as well as where it is.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection

• Input: an image.

• Output: bounding boxes containing depicted objects.

• Each image contains a different number of objects (outputs).

• Typical approach: train a specialized classifier and deploy

in sliding-window style to detect all object of that class.

• Very inefficient, quite ineffective.

• Goal: combine classification and localization into a single

architecture for multiple, multiclass object detection.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection with CNNs

• Deep Learning (DL) approach: train a classifier on, say,

1000 classes of ILSVRC.

• OverFeat (2013) was one of the first DL approaches to

object detection. Its convolutional method made multi-scale

sliding window efficient.

• Based on AlexNet architecture.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection with CNNs

Sermanet, Pierre, et al. "Overfeat: Integrated recognition, localization and detection using convolutional networks." International Conference on Learning

Representations (ICLR2014), CBLS, April 2014. 2014.

Overfeat: Object detection at

increasing image resolutions

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Object detection with CNNs

• Impact of Deep Learning.

• Pascal VOC

(object detection)

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Imaging for drone safety

• Human crowd detection for safe autonomous drones

• Emergency landing site detection.

Page 34: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd detection for safe autonomous drones

• Detect where crowd exists.

• Comply with legislation.

• Detect emergency landing points.

• Provide heatmaps of the estimated probability of crowd presence in

each location.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd detection for safe autonomous drones

Page 36: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd detection for safe autonomous drones

• Limited previous efforts on crowd detection, using computer

vision techniques.

• Crowded scenes are considered in related research works

involving crowds, e.g.,:

• crowd understanding,

• crowd counting,

• human detection and tracking in crowds.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd detection for drone flight safety using CNNs

• In [1], a method utilizing Convolutional Neural Networks

(CNNs) for crowd detection is proposed.

• Two approaches:

• transforming a pre-trained CNN to a fast, fully-convolutional network,

• devising a two-loss-training model, enhancing the separability of the crowd

and non-crowd classes.

[1] Tzelepi, Maria, and Anastasios Tefas, "Human Crowd Detection for Drone Flight Safety Using Convolutional Neural Networks." in European

Signal Processing Conference (EUSIPCO), Kos, Greece, 2017.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd detection for drone flight safety using CNNs

• Provide lightweight models, as imposed by the computational

restrictions of the application.

• Effectively distinguish between crowded and non-crowded scenes.

• Provide crowd heatmaps to semantically enhance flight maps by

defining no-fly zones.

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd heatmaps

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Human crowd heatmaps

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

XML Schema

Production Planning Schema

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Conclusions

• MULTIDRONE is aiming at defining and developing

innovative multi-actor autonomous system for UAV-based

media production

• Many challenges, here we focused on two

• Drone cinematography principles for media production

planning

• Target detection for automated tracking using DL

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This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)

Page 45: MULTIPLE DRONE CINEMATOGRAPHY · • A couple of Framing Shot Types deal with two or more subjects / targets: • 2 Shot / 3 Shot: 2/3 subjects appear on frame, equally visible (typically

This project has received funding from the European Union’s Horizon 2020 research

and innovation programme under grant agreement No 731667 (MULTIDRONE)