Sriparna Saha

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The aim of this novel work is to recognize 12 health care linked gestures from young individuals of 20-40 years of age group. Due to constant sitting in a specific posture for deskbound jobs, functioning of joints and muscles of persons are deteriorated. The scope of this work is to recognize the early stage symptoms of those physical disorders and notify(More)
positive or negative with its intensity information. A total of twenty three features have been extracted based on the distance between different parts of the upper human body, the velocity and acceleration generated along with the angle between different joints. The proposed algorithm gives a high recognition rate of 86.8% using SVM.
— 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)
—Sign language interpretation is gaining a lot of research attention because of its social contributions which is proved to be extremely beneficial for the people suffering from hearing or speaking disabilities. This paper proposes a novel image processing sign language detection framework that employs MAdaline network for classification purpose. This paper(More)