An Artificial Approach of Video Object Action Detection by Using Gaussian Mixture Model

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2016 by IJETT Journal
Volume-42 Number-2
Year of Publication : 2016
Authors : Sneha Jain, Gagan Vishwakarma, Yogendra Kumar Jain
DOI :  10.14445/22315381/IJETT-V42P212


Sneha Jain, Gagan Vishwakarma, Yogendra Kumar Jain "An Artificial Approach of Video Object Action Detection by Using Gaussian Mixture Model", International Journal of Engineering Trends and Technology (IJETT), V42(2),49-55 December 2016. ISSN:2231-5381. published by seventh sense research group

The digital data processing plays an important role in today’s world. This attracts many researchers to solve different issues of video object processing field. This paper works on one of significant issue of video objects detection with action recognition in videos and it proposes an artificial approach to detect action of the video object. The working methodology is consisting of the separation of foreground, background features in videos and the training of the system. Foreground and background features of the videos are separated by using gaussian mixture model. The training and action recognition of detected object is done by error back propagation neural network. The experiments are carried out on real datasets, which further calculate results of comparisons. The comparisons are taken out between experimental results and existing action detection methods. Results show that proposed work reduces the execution time and increases the pixel localization parameter.


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Action detection, Feature extraction, Image processing, Object tracking, Neural network.