TAILIEUCHUNG - Báo cáo " Motion detection and tracking algorithms in video streams "

Moving objects detection and tracking in video stream are basic fundamental and critical tasks in many computer vision applications. We have presented in this paper effectiveness increase of algorithms for moving objects detection and tracking. For this, we use additive minimax similarity function. Background reconstruction algorithm is developed. Moving and tracking objects detection algorithms are modified on the basis of additive minimax similarity function. Results of experiments are presented according to time expenses of the moving object detection and tracking. . | VNU Journal of Science Mathematics - Physics 25 2009 143-151 Motion detection and tracking algorithms in video streams R. Bogush A. Kastryuk N. Brovko D. Hlukhau Polotsk State University Blochin str. 29 Novopolotsk Belarus 211440 Received 30 June 2009 Abstract. Moving objects detection and tracking in video stream are basic fundamental and critical tasks in many computer vision applications. We have presented in this paper effectiveness increase of algorithms for moving objects detection and tracking. For this we use additive minimax similarity function. Background reconstruction algorithm is developed. Moving and tracking objects detection algorithms are modified on the basis of additive minimax similarity function. Results of experiments are presented according to time expenses of the moving object detection and tracking. Keywords Moving Objects Detection Tracking Background Reconstruction Minimax Similarity Function 1. Introduction Moving objects detection in video streams is a key fundamental and critical task in many computer vision applications including video surveillance as well as people tracking gesture recognition in human-machine interface traffic monitoring and so on 1 2 . Detection of moving object should be characterized by some important features high precision in case of noise components presence on the video streams flexibility in different scenarios indoor outdoor or different light conditions efficiency in order for detection to be provided in real-time. Basic methods for motion detection in a continuous video stream are optical flow frame difference and background subtraction. All of them are based on comparing of the current video frame with one from the previous frames or with background. The most widely adopted approach for moving object detection with fixed camera is based on background subtraction. For frame comparison of a video information a row of measures are used as unit for measurement of similarity images 4 . Normalized .

• Báo cáo khoa học
• Motion detection
• Mathematics
• Physics
• Scientific reports
• scientific studies
• natural sciences
• Video smoke detection
• Fire detection
• Motion features
• Optical flow
• Neural network
• Color Features
• Velocity detection
• Motion blur image
• Radon transformation
• 2D image
• Camera manufacturer’s data
• Moving object detection
• Pedestrian detection
• Fusion method
• Oriented Gradients
• Background Subtraction
• báo cáo hóa học
• công trình nghiên cứu về hóa học
• tài liệu về hóa học
• cách trình bày báo cáo
• báo cáo khoa học
• Fall people
• Fall detection
• Real time motion monitoring
• Wireless fall warning system
• Warning system
• BMC Bioinformatics
• Secondary structure detection
• Protein motion simulations
• Biological meaning
• Simulation algorithms
• Tạp chí tin học
• Điều khiển học
• Smoke detection
• Video sequences
• Weber contrast analysis