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Motion Estimation and Tracking of Hand Using Harris-Laplace Feature Based Approach


Affiliations
1 Department of Electronics and Communication, SATI, Vidisha, M.P, India
2 Department of Computer Science and Engineering, Samrat Ashok Technological Institute (Engineering College), Vidisha, M. P., India
     

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Hand is now being accepted as most promising, natural and simple modality in real time applications.  There are many natural factors, like shape and speed and environmental factor, like view-point, scale etc. which effect deeply in efficiency of Dynamic Hand Gesture Recognition System. The current–state of art is still faces many challenges in finding efficient tracking mechanism. This paper aims to present a novel approach of using Harris- Laplace to visually locate and track hand in each frame. The paper emphasizes that detection of ‘corners’ as   interest points show high performance and less computation, in case of Hand recognition. The results are also compared with other local features like, SIFT and SURF techniques and found that in case of dynamic hand tracking ‘Harris –Laplace’ detection shows better performance.


Keywords

Dynamic Hand Gesture Recognition, Feature Descriptors, SIFT, SURF, Harris-Laplace.
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  • Motion Estimation and Tracking of Hand Using Harris-Laplace Feature Based Approach

Abstract Views: 245  |  PDF Views: 3

Authors

Richa Golash
Department of Electronics and Communication, SATI, Vidisha, M.P, India
Yogendra Kumar Jain
Department of Computer Science and Engineering, Samrat Ashok Technological Institute (Engineering College), Vidisha, M. P., India

Abstract


Hand is now being accepted as most promising, natural and simple modality in real time applications.  There are many natural factors, like shape and speed and environmental factor, like view-point, scale etc. which effect deeply in efficiency of Dynamic Hand Gesture Recognition System. The current–state of art is still faces many challenges in finding efficient tracking mechanism. This paper aims to present a novel approach of using Harris- Laplace to visually locate and track hand in each frame. The paper emphasizes that detection of ‘corners’ as   interest points show high performance and less computation, in case of Hand recognition. The results are also compared with other local features like, SIFT and SURF techniques and found that in case of dynamic hand tracking ‘Harris –Laplace’ detection shows better performance.


Keywords


Dynamic Hand Gesture Recognition, Feature Descriptors, SIFT, SURF, Harris-Laplace.

References