Occlusion detection and processing using optical flow and particle filter

Askar, Wesam; Elmowafy, Osama; Ralescu, Anca; Youssif, Aliaa A. A.; Elnashar, Gamal

doi:10.1504/ijaip.2020.10025745

Cited by 2 publications

(1 citation statement)

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“…Mai Thanh Nhat Truong [8] proposed a saliency-based weighted color histogram to better distinguish the target from the background. Askar [9] proposed the method of combining the particle filter and optical flow and changing the tracking route at different states to complete the antiocclusion tracking. Pranab [10] proposed the particle filter with a mean-shift model to change the particle distribution at the occlusion state and improve the success rate of the re-searching after occlusion.…”

Section: Introductionmentioning

confidence: 99%

Position reset and hybrid feature based particle filter tracking for large-size and long-term full occlusion

CAO

CHENG

LIU

et al. 2023

Third International Conference on Computer Vision and Information Technology (CVIT 2022)

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Object tracking plays an important role in the computer vision field and has many applications such as video surveillance and vehicle navigation. But the occlusion problem is one of the most challenging problems in the applications. Although there are many approaches in the object tracking field that focus on dealing with occlusion scenes, the occlusion with large size barriers and long occlusion time still cannot be solved. To handle the problems, this paper proposes a reliable tracking method based on particle filter focus on long-term full occlusion with large size barriers. In this paper the large size is defined as pixel width from 350 to 600 in fixed resolution images. and the long term is defined as occlusion frame number from 180 to 600. First, this paper proposed a particle position reset module to replace the resampling process during the occlusion periods to solve the problem of losing the target after occlusion. In addition, a hybrid feature based likelihood model is proposed for the occlusion happening and ending judgments. Experiments on the extreme occlusion situation sequences demonstrate the reliability and accuracy of the proposed work on these challenging scenes. The algorithm finally implements the average 92% success rate at the tested sequences.

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Section: Introductionmentioning

confidence: 99%