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A Scheme of Visual Object Tracking for Human Activity Recognition in Social Media Analytics

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Information, Communication and Computing Technology (ICICCT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 750))

Abstract

Human action recognition is an open challenge in computer vision area. It means recognizing the action of human in a video. It can be divided into two steps, first step is extracting feature from video and second step is to use a classifier to find tag for the action like jump, walk, sit, hand waving etc. It is very challenging task due noise, occlusion, motion blur, and camera movement. Actions are performed by a single person or more than one person at a time. Activity recognition now a days is having a lot importance due to its many of the advantages like surveillance systems at airport, patient monitoring system, care of elderly people etc. are very few to mention. In this work we proposed Ohta color space along with RGB channel which used with LBP texture. We are extracting texture feature with the help of local binary pattern. It is used five major non uniform rotational invariant LBP and Ohta along with RGB color for the representation of the target. This scheme successfully extract the color, edge and corner information. Our proposed method maintains a trade-off between exactness of object detection and ensure that it is faster. The fusion of rotationally invariant LBP and Ohta color features make this scheme useful in object tracking for specific human activity recognition. The fused features are tested by mean shift tracker.

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Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667, India

    Naresh Kumar

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  1. Naresh Kumar
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Correspondence to Naresh Kumar .

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Editors and Affiliations

  1. Indian Institute of Technology Delhi, New Delhi, India

    Saroj Kaushik

  2. Delhi Technological University, Delhi, India

    Daya Gupta

  3. Jagan Institute of Management Studies, Delhi, India

    Latika Kharb

  4. Jagan Institute of Management Studies, Delhi, India

    Deepak Chahal

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© 2017 Springer Nature Singapore Pte Ltd.

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Naresh Kumar (2017). A Scheme of Visual Object Tracking for Human Activity Recognition in Social Media Analytics. In: Kaushik, S., Gupta, D., Kharb, L., Chahal, D. (eds) Information, Communication and Computing Technology. ICICCT 2017. Communications in Computer and Information Science, vol 750. Springer, Singapore. https://doi.org/10.1007/978-981-10-6544-6_19

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  • DOI: https://doi.org/10.1007/978-981-10-6544-6_19

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6543-9

  • Online ISBN: 978-981-10-6544-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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