Tracking Multiple Objects with Locally Adaptive Generalized Optimum Correlation Filters
Vitaly Kober, Alexey Nikolaevich Ruchay, В. Н. Карнаухов · Journal of Communications Technology and Electronics · 2020
—An algorithm for tracking multiple objects using locally adaptive generalized filtering is proposed. The tracking algorithm is invariant to geometric transformations of objects, partial occlusion of objects, nonuniform illumination of scene, and additive noise in scene images. The proposed system utilizes generalized optimal correlation filters and a prediction scheme based on the kinematic model of objects motion. With the help of iterative training, the training system can be adapted to current scene changes. The performance of the proposed algorithm is compared with that of the state-of-the-art visual tracking algorithms on known databases in terms of commonly accepted quality metrics and processing time.