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Felzenszwalb, P., McAllester, D. and Ramanan, D. (2008) A Discriminatively Trained, Multiscale, Deformable Part Model. 2008 IEEE Conference on Computer Vision and Pattern Recognition, Anchorage, 23-28 June 2008, 1-8.
https://doi.org/10.1109/cvpr.2008.4587597

has been cited by the following article:

• TITLE: A Distributed Particle Filter Applied in Single Object Tracking

  AUTHORS: Di Wang, Min Chen

  KEYWORDS: Distributed System, Particle Filter, Single Object Tracking

  JOURNAL NAME: Journal of Computer and Communications, Vol.12 No.8, August 22, 2024

  ABSTRACT: Visual object-tracking is a fundamental task applied in many applications of computer vision. Particle filter is one of the techniques which has been widely used in object tracking. Due to the virtue of extendability and flexibility on both linear and non-linear environments, various particle filter-based trackers have been proposed in the literature. However, the conventional approach cannot handle very large videos efficiently in the current data intensive information age. In this work, a parallelized particle filter is provided in a distributed framework provided by the Hadoop/Map-Reduce infrastructure to tackle object-tracking tasks. The experiments indicate that the proposed algorithm has a better convergence and accuracy as compared to the traditional particle filter. The computational power and the scalability of the proposed particle filter in single object tracking have been enhanced as well.