• Arpitha.K
• Dr.M.V.Vijaya Kumar

In computer vision technology video surveillance seems to be one of the hot research topic where it exactly detects the objects, recognize the objects and track the objects from a given sequence of image(video).Apart from this it also aims at understanding and delivering of the objects behavior by replacing the old method of human being monitoring the cameras to detect and track the objects and also this technique is one among the important and challenging tasks of the computer vision which involves detection and tracking of the objects from a video sequence. To detect the vehicle from the dashboard video using machine learning techniques we use already existing datasets like GTI and KITTI vision. In this paper we use techniques of machine learning computer vision such as spatial binning, HOG, color histograms for extracting features and SVM is used as training classifier and other techniques such as sliding window, heat maps and many other techniques will be used to detect the object (vehicle) from given dashboard video and resultant is also saved in the video format. Apart from vehicle detection from the dash board video has to be tracked too this can be achieved with the combination of Kalman Filter and Optical Flow algorithm.

Hog, Spatial binning, Support Vector Machines.

"VEHICLE DETECTION AND TRACKING FROM STATIONARY AND VIDEOS USING A HIGH RESOLUTION IMAGES BY MACHINE LEARNING AND COMPUTER VISION APPROACH.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.361-364, June 2019, Available :http://www.jetir.org/papers/JETIR1906O54.pdf

"VEHICLE DETECTION AND TRACKING FROM STATIONARY AND VIDEOS USING A HIGH RESOLUTION IMAGES BY MACHINE LEARNING AND COMPUTER VISION APPROACH.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp361-364, June 2019, Available at : http://www.jetir.org/papers/JETIR1906O54.pdf