Journal Title : International Journal of Modern Trends in Engineering and Science
Paper Title : VISUAL BASED TRESPASSER AND FAINT DETECTION FOR SURVEILLANCE APPLICATION WITH POSTURE RECOGNITION
Volume 04 Issue 04 2017
ISSN no : 2348-3121
Page no: 123-126
Abstract – An efficient surveillance system for faint and trespasser detection system is designed. In this method, the object and features are extracted from the captured scene which includes the head and leg features for a robust indoor application. Then, the status of the people is predicted based on that features. The features are extracted by using HOG and LBP algorithms. This paper proposes a proficient visual based home reconnaissance framework for security and medicinal services purposes. The proposed reconnaissance framework is used to identify trespasser or blacked out people in an indoor area, for example, private property, home and old society’s inside. In this framework, a remote webcam is used to catch the required scene. Then, the scene is nourished by means of a remote switch into a PC for picture preparing, trespasser or black out recognition and caution enactment. The human outline reconciliation incorporates the use of head, leg what’s more, proportion identification highlights for a more strong application. Trial comes about demonstrate that the proposed reconnaissance framework, in an indoor situation with a decent light condition accomplishes high precision of 96.5% in trespasser recognition and swoon recognition.
Key Words – HOG and LBP algorithms, surveillance system
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