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A silhouette based novel algorithm for object detection and tracking using information fusion of video frames

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Abstract

Object detection and tracking has been gaining widespread interest and significance with rate of increase in technology towards development of new gadgets. From a continuous video locating a particular object and tracking it is a sequence of process which involves segmentation, preprocessing, extracting the features, finally clustering for recognizing the particular object. This research works highlights the maximum capability of results in order to detect and track the object using a set of algorithms for detection mixed along with the optimization algorithms for better computation time and minimum of errors. The proposed work exploits the contour extraction followed by computation of dissimilarity measure between two signals. A single video sequence partitioned into frames has been optimized for an efficient tracking as evident from the end results.

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Funding

Funding was provided by National Natural Science Foundation of China (Grant Nos. 61402544, 61671484, 61702563).

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Authors and Affiliations

  1. College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless Communications, South-Central University for Nationalities, Wuhan, China

    Xiaoping Jiang, Jing Sun, Hao Ding & Chenghua Li

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  1. Xiaoping Jiang
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  2. Jing Sun
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  3. Hao Ding
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  4. Chenghua Li
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Correspondence to Jing Sun.

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Jiang, X., Sun, J., Ding, H. et al. A silhouette based novel algorithm for object detection and tracking using information fusion of video frames. Cluster Comput 22 (Suppl 1), 391–398 (2019). https://doi.org/10.1007/s10586-018-2108-0

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  • DOI: https://doi.org/10.1007/s10586-018-2108-0

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