Cluster Computing

, Volume 22, Supplement 1, pp 391–398 | Cite as

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

  • Xiaoping Jiang
  • Jing SunEmail author
  • Hao Ding
  • Chenghua Li


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.


Detection and tracking Contour extraction Point labelling Dissimilarity measure 



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


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Xiaoping Jiang
    • 1
  • Jing Sun
    • 1
    Email author
  • Hao Ding
    • 1
  • Chenghua Li
    • 1
  1. 1.College of Electronics and Information Engineering, Hubei Key Laboratory of Intelligent Wireless CommunicationsSouth-Central University for NationalitiesWuhanChina

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