multi object tracking | presentation 1 | id 103001
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Multi-Object Trackingusing Computer Vision
Heaven's Light is Our GuideRajshahi University of Engineering and
TechnologyDepartment of Computer Science and
Engineering
Presented byMd. Minhazul HaqueRoll # 103001Dept. of CSERUET
Supervised byMd. Arafat Hossain
Assistant ProfessorDept. of CSE
RUET
August 04, 2015
Table of Contents❏ Object❏ Object Tracking❏ Application❏ Background Study❏ How it works❏ Multi-Object Tracking❏ Solution❏ Future Works
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The Cars
August 04, 2015Image Courtesy: Flickr
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ObjectObject
❏ A group of pixels with similar property❏ A blob or reign of an image
Anything can be an Object❏ A ball❏ A car❏ A bird❏ Even you!
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Objects (cont.)
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A bird A car
A human
Image Courtesy: 4freephotos
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Object Tracking❏ Locate Objects over time❏ Save Object List into memory❏ Set unique ID to each Object❏ Loop until media/input ends
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Applications of Object TrackingObject Tracking could be helpful regarding -
❏ Apply Security Policies❏ Biomedical Research❏ Vehicle Routing❏ Drone Controls❏ Smart Car
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Image Courtesy: ImImg, SchoolOfMotoring
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Background Study❏ Contour-Based Object Tracking with
Occlusion Handling- Alper Yilmaz, Xin Li, Mubarak Shah, IEEE
❏ Fast and Automatic Video Object Segmentation and Tracking- Changick Kim and Jenq-Neng Hwang
❏ Kernel-Based Object Tracking- Dorin Comaniciu, Visvanathan Ramesh, Peter Meer, IEEE
❏ Object Tracking Using CamShift Algorithm and Multiple Quantized Feature Spaces- John G. Allen, Richard Y. D. Xu, Jesse S. Jin, University of Sydney
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∞
How Object Tracking Works
Tracking = (Detection + Recognition + Processing)
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Image Courtesy: Shakthydoss, Dodlive, Virus-IT
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Steps of Object Tracking
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Start Initialize source media
Apply BGS
Apply Contour DetectionGet Object List
Track Objects
Update Objects
Delete Objects
Add Objects
Streamof frames
Get a frame
Loop untilend of media/frame
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Object Tracking Methods❏ CamShift
Constantly Adaptive Mean Shift, Histogram based Tracker
❏ Kalman FilterLinear Quadratic Estimation developed by Rudolf E.
Kálmán
❏ Particle FilterMonte Carlo method based on probability
densities
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CamShift❏ Known as Constantly Adaptive
MeanShift❏ Calculates Shift Vector of Object❏ Saves Object Histogram into
memory❏ Looks for Object in all possible
directions from current position❏ Search area is expanded if Object
not found
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CamShift (cont.)
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Position 1All OK
Position 2Found inside search
areaPosition 3
Search area expanded
Search area❏ How CamShift works
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CamShift (cont.)Pros
❏ Tracks object faster❏ Easy to implement
Cons❏ Color based motion
tracker❏ Loses track easily when
similar colored objects are nearby
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Image Courtesy: Cliparthunt, Vectors4all
Founda track!
We are lost!
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Kalman Filter❏ Kernel based estimation algorithm❏ Uses 3 position matrix
1.Previous Position2.Current Position3.Predicted Position
❏ Updates all of them continuously
Predicted = K × Current + (K-1) × Previous
K = Kalman Filter Gain
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Kalman Filter (cont.)
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Position 1All OK
Position 2Calculate Gain K
Position 3Predict new position
❏ How Kalman Filter works
Gain at K-1
Predicted Gain at K
Update Gain asslightly mismatched
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Kalman Filter (cont.)Pros
❏ Mathematically precise❏ Tracks rouge objects❏ Removes noise from data
Cons❏ Complex to implement❏ Position based estimator
algorithm
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Image Courtesy: PMacStrong
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Multi-Object Tracking
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Why do we need Multi-Object Tracking?
❏ Real world has more Objects to track at a time (i.e. a highway)
❏ CamShift or Kalman Filter cannot handle Multi-Object Tracking alone
❏ Noise and unwanted Object makes tracking more challenging
❏ A new system needs to be implemented
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Multi-Object Tracking (cont.)
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Photo taken at RUET CampusExpected Multi-Object Tracking System
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❏ More feature extraction❏ Motion❏ Object Size❏ Object Orientation
❏ Add fallback tracking algorithm
❏ Better Background Subtraction
❏ Occlusion Handling
Solution?
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Image Courtesy: RockyTopSportsWorld
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❏ Collect datasets (videos of highway, campus area etc.)
❏ Implement new model for Multi-Object tracking
❏ Compare BGS models❏ Create a GUI for easy handling
Future Works
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Thank you, everyone!