NDLI: K-means based multiple objects tracking with long-term occlusion handling

Content Provider	IET Digital Library
Author	Shehzad, Muhammad Imran Shah, Yasir A. Mehmood, Zahid Malik, Abdul Waheed Azmat, Shoaib
Abstract	This study presents a novel multiple objects tracking (MOT) approach that models object's appearance based on K-means, while introducing a new statistical measure for association of objects after occlusion. The proposed method is tested on several standard datasets dealing complex situations in both indoor and outdoor environments. The experimental results show that the proposed model successfully tracks multiple objects in the presence of occlusion with high accuracy. Moreover, the presented work has the capability to deal long term and complete occlusion without any prior training of the shape and motion model of the objects. Accuracy of the proposed method is comparable with that of the existing state-of-the-art techniques as it successfully deals with all MOT cases in the standard datasets. Most importantly, the proposed method is cost effective in terms of memory and/or computation as compared with that of the existing state-of-the-art techniques. These traits make the proposed system very useful for real-time embedded video surveillance platforms especially those that have low memory/compute resources.
Starting Page	68
Ending Page	77
Page Count	10
ISSN	17519632
Volume Number	11
e-ISSN	17519640
Issue Number	Issue 1, Feb (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/11/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0156
Journal	IET Computer Vision
Publisher Date	2016-09-13
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique K-means Based Multiple Objects Tracking Long-term Occlusion Handling MOT Approach Motion Model Object Tracking Optical, Image And Video Signal Processing Real-time Embedded Video Surveillance Platform Standard Dataset State-of-the-art Technique Statistical Analysis Statistical Measure Statistics Video Surveillance
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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