A Robust Algorithm for Real Time Tracking With Optical Flow

Abstract

Object tracking is a troublesome undertaking and significant extent in data processor perception and image handling community. Some of the applications are protection surveillance, traffic monitoring on roads, offense detection and medical imaging. In this paper a recent technique for tracking of moving object is intended. Optical flow information authorizes us to know the displacement and speed of objects personate in a scene. Apply optical flow to the image gives flow vectors of the points to distinguishing the moving aspects. Optical flow is accomplished by Lucas canade algorithm. This algorithm is superior to other algorithms. The outcomes reveals that the intend algorithm is efficient and accurate object tracking method. This paper depicts a smoothing algorithm to track the moving object of both single and multiple objects in real time. The main issue of high computational time is greatly reduced in this proposed work

Stereo Vision-Based Relative Position and Attitude Estimation of Non-Cooperative Spacecraft

“…To make full use of time-sequential information in the image, this study proposes to use the Lucas-Kanade optical flow algorithm [31], as illustrated in Figure 5, to track and manage the feature points between frames. It saves the feature point information for a certain period and discards the feature points whose tracking is lost or the tracking time exceeds the threshold.…”