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RISS 인기검색어
- 검색키워드
- 저자 : ( Kajal Singh ) (검색결과 3 건)
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Kajal Sharma,김성관,Manu Pratap Singh 한국정밀공학회 2012 International Journal of Precision Engineering and Vol. No.
Stereo vision cameras are widely used for finding a path for obstacle avoidance in autonomous mobile robots. The Scale Invariant Feature Transform (SIFT) algorithm proposed by Lowe is used to extract distinctive invariant features from images. While it has been successfully applied to a variety of computer vision problems based on feature matching including machine vision, object recognition, image retrieval, and many others, this algorithm has high complexity and long computational time. In order to reduce the computation time, this paper proposes a SIFT improvement technique based on a Self-Organizing Map (SOM) to perform the matching procedure more efficiently for feature matching problems. Matching for multi-dimension SIFT features is implemented with a self-organizing map that introduces competitive learning for matching features. Experimental results on real stereo images show that the proposed algorithm performs feature group matching with lower computation time than the SIFT algorithm proposed by Lowe. We performed experiments on various set of stereo images under dynamic environment with different camera viewpoints that is based on rotation and illumination conditions. The numbers of matched features were increased to double as compared to the algorithm developed by Lowe. The results showing improvement over the SIFT proposed by Lowe are validated through matching examples between different pairs of stereo images. The proposed algorithm can be applied to stereo vision based robot navigation for obstacle avoidance, as well as many other feature matching and computer vision applications.
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Sharma, Kajal,Kim, Sung Gaun,Singh, Manu Pratap 한국정밀공학회 2012 International Journal of Precision Engineering and Vol.13 No.8
Stereo vision cameras are widely used for finding a path for obstacle avoidance in autonomous mobile robots. The Scale Invariant Feature Transform (SIFT) algorithm proposed by Lowe is used to extract distinctive invariant features from images. While it has been successfully applied to a variety of computer vision problems based on feature matching including machine vision, object recognition, image retrieval, and many others, this algorithm has high complexity and long computational time. In order to reduce the computation time, this paper proposes a SIFT improvement technique based on a Self-Organizing Map (SOM) to perform the matching procedure more efficiently for feature matching problems. Matching for multi-dimension SIFT features is implemented with a self-organizing map that introduces competitive learning for matching features. Experimental results on real stereo images show that the proposed algorithm performs feature group matching with lower computation time than the SIFT algorithm proposed by Lowe. We performed experiments on various set of stereo images under dynamic environment with different camera viewpoints that is based on rotation and illumination conditions. The numbers of matched features were increased to double as compared to the algorithm developed by Lowe. The results showing improvement over the SIFT proposed by Lowe are validated through matching examples between different pairs of stereo images. The proposed algorithm can be applied to stereo vision based robot navigation for obstacle avoidance, as well as many other feature matching and computer vision applications.
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Safeguarding Industrial Workers in Summer: A Thermochromic Approach to Assessing Work Intensity
( Sae Han Hwang ),( Hyun Wook Jo ),( Tharun Mario R ),( Kajal Singh ),( Min Seung Nam ),( Murali Subramaniyam ) 한국감성과학회 2023 한국감성과학회 국제학술대회(ICES) Vol.2023 No.-
This research presents the possibility of analyzing the work intensity or effort of industrial workers during the summer using thermochromic pigments. In the summer season, elevated temperatures and heat waves, combined with intense physical exertion, can lead to illnesses and life-threatening conditions for industrial workers. Therefore, we propose implementing a safety management system using thermochromic dyes to facilitate visible measurements for supervisors. To accomplish this, we dyed clothing with thermochromic pigments and assessed factors such as the appropriate color and clarity through a survey.
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