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Recognition of human activities from still image using novel classifier

The quest for recognizing human activities and categorizing their features from still images using efficient and accurate classifier is never ending. This is more challenging than extracting information from video due to the absence of any prior knowledge resembling frames stream. Human Activities R...

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Main Authors: Sulong, Ghazali, Mohammedali, Ammar
Format: Article
Published: Asian Research Publishing Network (ARPN) 2015
Subjects:
T Technology (General)
Online Access:http://eprints.utm.my/id/eprint/55226/
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spelling my.utm.552262016-09-04T01:12:24Z http://eprints.utm.my/id/eprint/55226/ Recognition of human activities from still image using novel classifier Sulong, Ghazali Mohammedali, Ammar T Technology (General) The quest for recognizing human activities and categorizing their features from still images using efficient and accurate classifier is never ending. This is more challenging than extracting information from video due to the absence of any prior knowledge resembling frames stream. Human Activities Recognition (HAR) refers to computer identification of specific activities to aid understanding of human behaviors in diversified applications such as surveillance cameras, security systems and automotive industry. We developed a novel model for classifier and used it in three main stages including preprocessing (foreground extraction), segmentation (background subtraction) to extract useful features from object and sort out these features by the classifier (classification). The model is further simulated using MATLAB programming. Our new classifier generates slightly different results for still image based on dataset INRIA and KTH for 780 images of (64*128) pixels format obtained from literature. The recognition rate of 86.2% for five activities such as running, walking, jumping, standing and sitting achieved by us is highly promising compared to the existing one of 85% over last decade. Asian Research Publishing Network (ARPN) 2015-01-01 Article PeerReviewed Sulong, Ghazali and Mohammedali, Ammar (2015) Recognition of human activities from still image using novel classifier. Journal of Theoretical and Applied Information Technology, 71 (1). pp. 115-121. ISSN 1992-8645
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology (General)
spellingShingle T Technology (General)
Sulong, Ghazali
Mohammedali, Ammar
Recognition of human activities from still image using novel classifier
description The quest for recognizing human activities and categorizing their features from still images using efficient and accurate classifier is never ending. This is more challenging than extracting information from video due to the absence of any prior knowledge resembling frames stream. Human Activities Recognition (HAR) refers to computer identification of specific activities to aid understanding of human behaviors in diversified applications such as surveillance cameras, security systems and automotive industry. We developed a novel model for classifier and used it in three main stages including preprocessing (foreground extraction), segmentation (background subtraction) to extract useful features from object and sort out these features by the classifier (classification). The model is further simulated using MATLAB programming. Our new classifier generates slightly different results for still image based on dataset INRIA and KTH for 780 images of (64*128) pixels format obtained from literature. The recognition rate of 86.2% for five activities such as running, walking, jumping, standing and sitting achieved by us is highly promising compared to the existing one of 85% over last decade.
format Article
author Sulong, Ghazali
Mohammedali, Ammar
author_facet Sulong, Ghazali
Mohammedali, Ammar
author_sort Sulong, Ghazali
title Recognition of human activities from still image using novel classifier
title_short Recognition of human activities from still image using novel classifier
title_full Recognition of human activities from still image using novel classifier
title_fullStr Recognition of human activities from still image using novel classifier
title_full_unstemmed Recognition of human activities from still image using novel classifier
title_sort recognition of human activities from still image using novel classifier
publisher Asian Research Publishing Network (ARPN)
publishDate 2015
url http://eprints.utm.my/id/eprint/55226/
_version_ 1643653733005918208
score 13.211869

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