International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Volume3,May 2016,

Topic : Human Tracking and Action Recognition Based on k-Nearest Neighbor Classifier

Authors:Shilpashree S || Dr. D.J.Ravi , Jagadeesh B

Abstract:Human tracking and Activity recognition is a field of computer vision which has shown great progress in the past decade. Starting from simple single person activities, research in activity recognition is moving towards more complex scenes involving multiple objects and natural environments. The main challenges in the task include being able to localize and recognize events in a video and deal with the large amount of variation in viewpoint, speed of movement and scale. It has gained more interest of late, among video processing community because they find various applications in automatic surveillance, monitoring systems, video indexing and retrieval, robot motion, human – computer interaction and segmentation. The proliferation of surveillance cameras and smart-phones has dramatically changed the video capture landscape. There is more video data generated each day than ever before, it is more diverse and its importance has reached beyond security and entertainment (e.g., healthcare, education, and environment).This project deals with the single person tracking and action recognition of that person. And also it deals with combining the advantages of both tracking and action recognition in a single framework. Here based on STIP single person tracking is done, kNN classifier is used for action classification and recognition. Finally, coding is done in Matlab..

Keywords: computer vision; STIP; detection; tracking; kNN; action recognition

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DOI: 01.1617/vol3iss5pid229


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Dr.Zhongfu Tan
National Professor,
North China Electric Power University,
CHINA


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