video tracking g. medioni, q. yu edwin lei maria pavlovskaia

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Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

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Page 1: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Video Tracking

G. Medioni, Q. Yu

Edwin LeiMaria Pavlovskaia

Page 2: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Goal

Track moving objects in a video stream

Page 3: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Linking frames

Each frame registered with a satellite image

Page 4: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Detecting Moving Regions

• A sliding window with the center frame as the reference

• Register each frame in the window to the reference

• A region is moving if it differs from the registered frames

• Moving regions are grouped into tracklets

Page 5: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Tracklet Association

Motion

• Target remains within a reasonable distance between frames

Appearance

• Target has similar color distribution between frames

Page 6: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Tracklet Evolution

Temporal moves• Change labels

Spatial moves• Change rectangles

at one instant

Page 7: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Merge

Page 8: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Pre-processing

Goal• Enhance given video before tracking

Methods• Auto levels• Adaptive auto levels

Page 9: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Auto Levels

Page 10: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Auto Levels

Histogram of pixel values

Page 11: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Auto Levels

Modified histogram

Page 12: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Auto Levels in Video

Concerns

• Algorithm should be fast

• Do not need to perform histogram computations for each frame

• Can not treat each channel separately

Page 13: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Adaptive auto levels

Page 14: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Adaptive auto levels

Page 15: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Adaptive auto levels

Page 16: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Minima cutoffs Maxima cutoffs

Page 17: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Adaptive Auto Levels

Page 18: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Post-processing

• Identify tracklets that are too short

• Highlight tracklets of interest

• Renumber tracklets

• Display tracklet labels

Page 19: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Highlighting Tracklets

• Identify tracklets that are too short

• Highlight tracklets of interest

Page 20: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Renumber tracklets

Page 21: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Displaying Tracklet Labels

Goal: intelligently display a label next to every tracklet box

Page 22: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Displaying Tracklet Labels

Desired specifications for label placement:

– Label must be near corresponding box

– Labels must be inside image boundary

– Labels should not overlap

– Labels should be far from other boxes

– Labels should be far from box corners

– Labels should not jump from frame to frame

– Algorithm must be fast

Page 23: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Final Result

Page 24: Video Tracking G. Medioni, Q. Yu Edwin Lei Maria Pavlovskaia

Thanks!