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1887

access icon free Robust tracking of multiple objects in video by adaptive fusion of subband particle filters

© The Institution of Engineering and Technology
Received 17/03/2018, Accepted 03/07/2018, Revised 17/06/2018, Published 30/07/2018

Tracking of moving objects in video sequences is an important research problem because of its many industrial, biomedical, and security applications. Significant progress has been made on this topic in the last few decades. However, the ability to track objects accurately in video sequences that have challenging conditions and unexpected events, e.g. background motion and shadows; objects with different sizes and contrasts; a sudden change in illumination; partial object camouflage; and low signal-to-noise ratio, remains an important research problem. To address such difficulties, the authors developed a robust multiscale visual tracker that represents a captured video frame as different subbands in the wavelet domain. It then applies N independent particle filters to a small subset of these subbands, where the choice of this subset of wavelet subbands changes with each captured frame. Finally, it fuses the outputs of these N independent particle filters to obtain final position tracks of multiple moving objects in the video sequence. To demonstrate the robustness of their multiscale visual tracker, they applied it to four example videos that exhibit different challenges. Compared to a standard full-resolution particle filter-based tracker and a single wavelet subband (LL)2-based tracker, their multiscale tracker demonstrates significantly better tracking performance.

Inspec keywords: image fusion; set theory; video signal processing; object tracking; image sequences; particle filtering (numerical methods)

Other keywords: moving object tracking; wavelet subband subset; robust multiple object tracking; independent particle filters; shadows; low signal-to-noise ratio; robust multiscale visual tracker; video sequences; adaptive subband particle filter fusion; partial object camouflage; captured video frame; background motion

Subjects: Video signal processing; Filtering methods in signal processing; Sensor fusion; Computer vision and image processing techniques; Combinatorial mathematics; Optical, image and video signal processing; Combinatorial mathematics

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