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Gesture Reco & Ditiop from video

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dc.contributor.author Nisha, Arifa
dc.contributor.author Sultana, Jihan
dc.date.accessioned 2014-12-02T09:28:45Z
dc.date.available 2014-12-02T09:28:45Z
dc.date.issued 5/3/2014
dc.identifier.uri http://dspace.ewubd.edu/handle/2525/1034
dc.description This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Electronics and Telecommunication Engineering of East West University, Dhaka, Bangladesh. en_US
dc.description.abstract Recognizing Human Actions from video is a challenging problem which has received much attention during the recent years due to its many applications in different fields. A reliable system capable of recognizing various human actions has many important applications such an human computer interaction,content-based video retrieval, visual surveillance, analysis of sports events and more. The problem of human action recognition from video sequence was addressed in this project. The aim is to develop an algorithm which can recognize low-level-actions from the input video sequences. For the purpose of evaluation we introduce a new video database of such low- level five human actions (walking,running jogging, boxing and hand clapping )performed by 25 people in four different dimensions. The presented results of action recognition justify the proposed method and demonstrate its advantage compared to other relative approaches for action reorganization. en_US
dc.language.iso en_US en_US
dc.publisher East West University en_US
dc.relation.ispartofseries ;ECE00003
dc.subject Gesture Record & Video en_US
dc.title Gesture Reco & Ditiop from video en_US
dc.type Thesis en_US


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