Sriparna Saha

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This work proposes gesture recognition algorithm for Indian Classical Dance Style using Kinect sensor. This device generates the skeleton of human body from which twenty different junction 3-dimensional coordinates are obtained. Here we require only eleven coordinates for the proposed work. Basically six joints coordinates about right and left hands and(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)
This novel work is aimed at the study of emotion recognition from gestures using Kinect sensor. The Kinect sensor along with Software Development Kit (SDK) generates the human skeleton represented by 3-dimensional coordinates corresponding to twenty body joints. Using the co-ordinates of eleven such joints from the upper body and the hands, a set of nine(More)
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 presents a method for automatic hand gesture recognition of 'Bharatanatyam' dance using Fuzzy L membership function based approach. Here, a 3-stage system has been designed. In the first stage, the hand of the dancer from background is isolated using Texture based segmentation and thus the contour of the hand is extracted by using Sobel edge(More)
The aim of this novel work is to recognize 12 health care linked gestures from young individuals of 2040 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)
With the growing interest in the domain of human computer interaction (HCI) these days, budding research professionals are coming up with novel ideas of developing more versatile and flexible modes of communication between a man and a machine. Using the attributes of internet, the scientists have been able to create a web based social platform for learning(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)
Currently, gesture recognition from continuous video sequences is one of the most exciting research areas. This paper proposes a novel HMM-based gesture recognition scheme that can be implemented for developing an improved HCI system capable of providing enhanced performance. This framework explores the high potential of Microsoft's Kinect sensor in gesture(More)