Video Detection and Tracking Using Extended Kalman Filter
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 4
Abstract
An efficient moving object segmentation algorithm suitable for real-time content-based multimedia communication systems is proposed in this paper. First, a background registration technique is used to construct a reliable background image from the accumulated frame difference information. The moving object region is then separated from the background region by comparing the current frame with the constructed background image. Finally, a post-processing step is applied on the obtained object mask to remove noise regions and to smooth the object boundary. Surveillance system can be used to detect and track the moving objects. First phase of the system is to detect the moving objects in the video and track the detected object. Second phase of the system detected different abnormal activities like crimes and robbery in ATM. In this paper, detection of the moving object has been done using simple background subtraction and tracking of single moving object has been done using Extended Kalman filter. Detection of abnormal activities can be done by using HOG (Histogram of Gradient) and IM (Illumination Mapping). The algorithm has been applied successfully on standard surveillance video datasets. The proposed method will uses multiple object detection method and event recognition techniques of computer vision.
Authors and Affiliations
Mr. Profun C. J, S. Kavitha
Keywords
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