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METHODS OF OBJECT TRACKING IN VISION SYSTEMS

This presentation explores various methods of object tracking in vision systems, emphasizing their applications in surveillance, video compression, motion capture, traffic control, driving assistance, and industrial uses. The discussion covers techniques such as gradient-based, feature-based, knowledge-based, and learning-based algorithms. Specific methodologies like the Mean Shift algorithm, similarity estimation using the Bhattacharyya coefficient, and the processing of image sequences are detailed. Finally, we evaluate the strengths and limitations of feature-based methods for robust object tracking.

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METHODS OF OBJECT TRACKING IN VISION SYSTEMS

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  1. Faculty of Electronics Institute of Telecommunication Military University of Technology METHODS OF OBJECT TRACKING IN VISION SYSTEMS Grzegorz Bieszczad Tutor: Tomasz Sosnowski ph.d.

  2. Applications • Surveillance • Video compression • Motion capture • Traffic control • Driving assistance • Industry METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  3. Object tracking fn-1 (x,y) fn (u1,v1) (u2,v2) (u3,v3) METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  4. Objects models database Image acquisition Object detection Tracking Algorithm Decision algorithms Vision system METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  5. Digital image Original image Image representation in points of certain luminosity Numeric representation METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  6. Methods revision • Gradient-based methods • Feature-based approaches. • Knowledge-based tracking algorithms. • Learning-based approaches. METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  7. Mean shift algorithm • Calculate model from given previous image in given location. • Initialize the location of the target in the current frame and calculate candidate model. • Estimate model and candidate similarity in neighbourhood. • Iteratively find the most similar area in target image. • Update the model METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  8. Model and candidate Frame 1 Frame 2 METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  9. Similarity estimation Bhattacharyya coefficient Bhattacharyya coefficient Taylor expansion METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  10. Mean shift procedure Local centroid (centre of mass) Mean shift operating area METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  11. Test sequence METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  12. Tracking in thermovision METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  13. Conclusions • Feature based method • Invariant to rotation and scale • Fast implementation • Tolerant to partial occlusions • Tolerant to changes of appearance • Limited range • Limited performance in low resolution images METHODS OF OBJECT TRACKING IN VISION SYSTEMS

  14. Thank you for Yourattention! METHODS OF OBJECT TRACKING IN VISION SYSTEMS

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