Sriparna Saha

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— This work aims at designing a fuzzy matching algorithm that would automatically recognize an unknown ballet posture from seventeen fundamental ballet dance primitives. A novel and simple 7-stage system is proposed to achieve the desired objective. Minimized skeletons of the dance postures are generated after performing skin color segmentation on them.(More)
— This paper introduces an algorithm for identification of dance video by recognizing posture from each frame for the purpose of e-learning. We are taking Indian classical dance 'Odissi' as the input. The twenty videos 'Chowkh' and 'Tribhangi' of 'Odissi' dance have been recognized using Kinect sensor, which is used for visual sensing. With the help of(More)
A simple method to detect gestures revealing muscle and joint pain is described in this paper. Kinect Sensor is used for data acquisition. This sensor only processes twenty joint coordinates in three dimensional space for feature extraction. The recognition part is achieved using a neural network optimized by Levenberg-Marquardt learning rule. A high(More)
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