Experiments in object tracking in image sequences

• Main Author: Law, Albert.
• Format: Others
• Language: en
• Published: McGill University 2007
• Subjects: Computer vision.
• Online Access: http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100229

This thesis explores three object tracking algorithms for image sequences. These algorithms include the ensemble tracker, the EM-like mean-shift colour-histogram tracker, and the wandering-stable-lost scale-invariant feature transform (WSL-SIFT) tracker. The algorithms are radically different from one another. Despite their differences, they are evaluated on the same publicly available, moderately sized, research data sets which include 129 test cases in 13 different scenes. The results aid in fostering an understanding of their respective behaviours and in highlighting their flaws and failures. Lastly, an implementation setup is described that is suited to large-scale, grid computing, batch testing of these algorithms. Results clearly indicate that none of the evaluated trackers are suited to general purpose use. However, one may intelligently choose a tracker for a well-defined application by analysing the known scene characteristics.