Analytical review on object segmentation and recognition

Abstract

The prime objective of this review is to analyze popular techniques used for object segmentation and recognition. In this paper various existing object segmentation and recognition methodologies have been systematically analyzed and presented. The importance of object segmentation can be in identifying the object in a video. It is majorly used in video surveillance system, in human activity recognition, in shadow detection which includes both static and moving objects. The object recognition also has various applications in the field of video stabilization, cell counting in bio-imaging and in automated vehicle parking system. Google's driverless car and Microsoft's Kinect System also uses object recognition methodologies for its implementation. We have concluded our findings with the various pros and cons of the existing methods and with the possibility of future research in this area.

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Cite this paper

@article{Sharma2016AnalyticalRO, title={Analytical review on object segmentation and recognition}, author={Anshika Sharma and Pradeep K. Singh and Palak Khurana}, journal={2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)}, year={2016}, pages={524-530} }