NDLI: Particle filter with occlusion handling for visual tracking

Content Provider	IET Digital Library
Author	Lin, Shinfeng D. Lin, Jia Jen Chuang, Chih Yao
Abstract	Visual tracking is widely used in many computer vision applications such as surveillance, traffic monitoring, robot vision, human behaviour analysis, and so on. Thus, visual tracking has attracted much attention in recent years. However, there are still some challenges needed to be solved. The main problems include illumination variation, scale variation, scene change, cluttered background, similar appearance, occlusion, and real time. To solve some issues in visual tracking, the authors propose a visual tracking method using particle filter with occlusion handling. This method contains three major parts: feature extraction, particles weighting, and occlusion handling. The patch-based appearance model is presented for occlusion handling, which contains two main features: colour and motion vector. For tracking failure, the authors also propose error recovery by using speeded up robust feature. In addition, the procedures of occlusion detection and model updating make their tracking more robust. Experimental results demonstrate the robustness and efficiency with challenging sequences. The comparative performance of the proposed method is shown as well.
Starting Page	959
Ending Page	968
Page Count	10
ISSN	17519659
Volume Number	9
e-ISSN	17519667
Issue Number	Issue 11, Nov (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/9/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2014.0666
Journal	IET Image Processing
Publisher Date	2015-09-17
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Cluttered Background Colour Vector Computer Vision Computer Vision And Image Processing Technique Computer Vision Application Feature Extraction Filtering Method in Signal Processing Illumination Variation Image Recognition Motion Vector Object Tracking Occlusion Handling Particle Filter Particle Weighting Patch-based Appearance Model Scale Variation Scene Change Similar Appearance Speeded Up Robust Feature Visual Tracking Method
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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