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Saturday, June 16th, 2012, 10:22 am

Tiny Set for Training of a Local Binary Patterns (LBP) Classifier

Based on cascade training with just 10 negatives and 20 positives (various cars and distances, poses). The real FPS rate is 6+; in the demo it’s decreased by the grabbing/streaming of screenshots for video capturing.

Initial Test

Zoom Changes and Local Binary Patterns Classifier Applied to Red Car

Car Tracking Test (Static With Panning)

6 FPS for tracking (1-minute video)

This video shows tracking of a car based on training with just 10 negatives and 20 positives (without cars like the one in this demo). The real FPS rate is around 6; grabbing and saving a video such as this (in real time) entails a massive performance penalty, so this demo cannot show just how smooth the tracking really is. For a classifier trained on more examples the performance will be comparable. If some code cruft is removed and the rendering gets optimised, 8 FPS seems reachable (this device generally captures raw video at about 10 FPS).

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