On Detection and Tracking of the Vehicles from the Real Time Video Stream Using Background Subtraction Process with Blob Tracker Algorithm (original) (raw)
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Video and image processing has been used for traffic surveillance, analysis and monitoring of traffic conditions in many cities and urban areas. Motion tracking is one of the most active research titles in computer vision field. This paper aims to Detect and track the vehicle from the video frame sequence The vehicle motion is detected and tracked along the frames using Optical Flow Algorithm and Background Subtraction technique. The distance travelled by the vehicle is calculated using the movement of the centroid over the frames. Many proposed motion tracking techniques are based on template matching, blob tracking and contour tracking. A famous motion tracking and estimation technique, optical flow, however, is not being widely used and tested for the practicability on traffic surveillance system. Thus, to analyze the reliability and practicability of it, this research project proposed the idea of implementing optical flow in traffic surveillance system, and will evaluate its performance. The results of tracking using optical flow is proving that optical flow is a great technique to track the motion of moving object, and has great potential to implement it into traffic surveillance system.
Vehicle Detection and Tracking from Video frame Sequence
Video and image processing has been used for traffic surveillance, analysis and monitoring of traffic conditions in many cities and urban areas. Motion tracking is one of the most active research titles in computer vision field. This paper aims to Detect and track the vehicle from the video frame sequence The vehicle motion is detected and tracked along the frames using Optical Flow Algorithm and Background Subtraction technique. The distance travelled by the vehicle is calculated using the movement of the centroid over the frames. Many proposed motion tracking techniques are based on template matching, blob tracking and contour tracking. A famous motion tracking and estimation technique, optical flow, however, is not being widely used and tested for the practicability on traffic surveillance system. Thus, to analyze the reliability and practicability of it, this research project proposed the idea of implementing optical flow in traffic surveillance system, and will evaluate its performance. The results of tracking using optical flow is proving that optical flow is a great technique to track the motion of moving object, and has great potential to implement it into traffic surveillance system.
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In PC vision, the most dynamic exploration points are visual reconnaissance in element scenes, particularly for people & vehicles. Wide range of promising applications incorporating human identification at some distance, controlling access in extraordinary ranges, measurements of group flux and investigating blockage or odd particles and for the utilization of numerous cameras intelligent reconnaissance and so much more. Visual observations in element scenes in the handling system incorporates various taking after stages i.e. characterization of moving item, depiction of the comprehensive particles, identifying the movement, displaying the whole situation, proof of human identification, at the end combining the information from different cameras. There are mixes of 2D & 3D images, therefore recognizing abnormalities and conducting forecast so that substance based recovery of reconnaissance features can be done. There are more things to understand about these like, common dialect portrayal, data combination from various sensors.