Online Object Tracking: A Benchmark

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Authors Yi Wu, Jongwoo Lim, Ming-Hsuan Yang
Journal/Conference Name IEEE Conference on Computer Vision and Pattern…
Paper Category
Paper Abstract Object tracking is one of the most important components in numerous applications of computer vision. While much progress has been made in recent years with efforts on sharing code and datasets, it is of great importance to develop a library and benchmark to gauge the state of the art. After briefly reviewing recent advances of online object tracking, we carry out large scale experiments with various evaluation criteria to understand how these algorithms perform. The test image sequences are annotated with different attributes for performance evaluation and analysis. By analyzing quantitative results, we identify effective approaches for robust tracking and provide potential future research directions in this field.
Date of publication 2013
Code Programming Language MATLAB
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