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dc.contributor.author Joseph, CN
dc.contributor.author Kokulakumaran, S
dc.contributor.author Srijeyanthan, K
dc.contributor.author Thusyanthan, A
dc.contributor.author Gunasekara, C
dc.contributor.author Gamage, CD
dc.date.accessioned 2016-05-26T09:35:12Z
dc.date.available 2016-05-26T09:35:12Z
dc.date.issued 2016-05-26
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/11772
dc.description.abstract The growth of technology continues to make both hardware and software affordable and accessible creating space for the emergence of new applications. Rapid growth in computer vision and image processing applications have been evident in recent years. One area of interest in vision and image processing is automated identification of objects in real-time or recorded video streams and analysis of these identified objects. An important topic of research in this context is identification of humans and interpreting their actions. Human motion identification and video processing have been used in critical crime investigations and highly technical applications usually involving skilled human experts. Although the technology has many uses that can be applied in every day activities, it has not been put into such use due to requirements in sophisticated technology, human skill and high implementation costs. This paper presents a system, which is a major part of a project called movelt (movements interpreted), that receives video as input to process and recognize gestures of the objects of interest (the human whole body). Basic functionality of this system is to receive video stream as input and produce outputs gesture analysis of each object through a staged process of object detection, classification, modeling, encoding and recognition of gestures as intermediate steps. en_US
dc.language.iso en en_US
dc.relation.uri http://dx.doi.org/10.1109/ICIINFS.2010.5578666 en_US
dc.source.uri http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5578666&abstractAccess=no&userType=inst en_US
dc.title A Framework for whole-body gesture recognition from video feeds en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Department of Computer Science and Engineering en_US
dc.identifier.year 2010 en_US
dc.identifier.conference 5th International Conference on Industrial and Information Systems (ICIIS-2010) en_US
dc.identifier.place Mangalore en_US
dc.identifier.pgnos pp. 430 - 435 en_US
dc.identifier.email nikkey@gmail.com en_US
dc.identifier.email kokulakumaran@gmail.com en_US
dc.identifier.email srijeyanthan@gmail.com en_US
dc.identifier.email athusy@gmail.com en_US
dc.identifier.email chulakag@uom.lk en_US
dc.identifier.email chandag@uom.lk en_US


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