NDLI: A dynamically selecting model to track a moving object

Content Provider	IEEE Xplore Digital Library
Author	Anmin Zhu Yanming Chen Xin Yi
Copyright Year	2013
Description	Author affiliation: Sch. of Comput. Sci. & Software Eng., Shenzhen Univ., Shenzhen, China (Anmin Zhu; Yanming Chen; Xin Yi)
Abstract	Based on the Lucas-Kanade optical flow method, a dynamically selecting model is proposed in this paper to track a moving object. This model is composed of an object model, a consistency constraint model, and a random sampling model. Based on the current image frame, the object model is used to calculate the relevant feature points for the next frame. The random sampling model is used to resample the feature points from the current frame and the relevant points on the next frame. By considering the consistency constraints in speed, direction and the object stability, the consistency constraint model is used to check the consistency for the feature points obtained by the object model, remove some unfit feature points, and add some new feature points obtained by the random sampling model. A stable tracking trajectory would be obtained during the tracking process using the proposed method. Simulation experiments comparing with traditional methods are conducted in different situations, such as illumination change, partial occlusion, high-speed motion, and object image with noise. The results show that the proposed object tracking method has better performance, which includes partial non-rigid object and varying velocity running object in real-time environment with robustness.
Sponsorship	IEEE Robot. Autom. Soc.
Starting Page	1728
Ending Page	1733
File Size	1596157
Page Count	6
File Format	PDF
ISBN	9781479927449
DOI	10.1109/ROBIO.2013.6739717
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Object tracking Optical imaging Stability analysis Target tracking Real-time systems Robustness dynamically selecting pattern recognition object tracking stability consistency constraints
Content Type	Text
Resource Type	Article

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