Open AccessPerformance Improvement of Hand Gesture Recognition By using Sparse Coding With Kinect V2 Sensors
Author(s) -
S.Chandra Sekhar*,
N.N. Mhala
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1976.0981119
Subject(s) - gesture , computer science , artificial intelligence , histogram , gratitude , gesture recognition , sparse approximation , computer vision , neural coding , segmentation , discriminative model , coding (social sciences) , support vector machine , pattern recognition (psychology) , image (mathematics) , mathematics , psychology , social psychology , statistics
This paper presents an important technique with improvement property for image identification intention. Here the important technique which is sparse coding representation acts as a major ROLE in achiveving One-short learning and real recognition of actions[1]. The implementation method based on mainly 3-D Histogram of prospect flow with Global Histograms of orientated Gradient .The major and most important of this method is to use imprison on major level regions from the given data sets . With this data then suggest a instantaneous to get video segmentation and video gratitude of hand gesture action by using linear SVMs.This paper mainly highlights the major role of sparse coding technique to stand for 3D proceedings [2] .From this paper we obtain very good results in an domestic dataset captured by Kinect V2 sensors together with hand gesture proceedings and complex hand gesture actions differing by small details.