منابع مشابه
Figure Tracking by Flies Is Supported by Parallel Visual Streams
Visual figures may be distinguished based on elementary motion or higher-order non-Fourier features, and flies track both. The canonical elementary motion detector, a compact computation for Fourier motion direction and amplitude, can also encode higher-order signals provided elaborate preprocessing. However, the way in which a fly tracks a moving figure containing both elementary and higher-or...
متن کاملReal Time Parallel Implementation of Particles Filter Based Visual Tracking
Particle filtering is a widely used method to solve vision tracking problems. However, to be able to run in real-time on standard architecture, the state vector used in the particle filter must remain small [1]. We propose a parallel implementation of a 3D tracking algorithm operating on a stereo video stream and running in real-time on a cluster architecture. We demonstrate the efficiency of t...
متن کاملVisual Tracking using Kernel Projected Measurement and Log-Polar Transformation
Visual Servoing is generally contained of control and feature tracking. Study of previous methods shows that no attempt has been made to optimize these two parts together. In kernel based visual servoing method, the main objective is to combine and optimize these two parts together and to make an entire control loop. This main target is accomplished by using Lyapanov theory. A Lyapanov candidat...
متن کاملVisual Tracking
In many video surveillance applications, cameras are fixed and we are interested in tracking the motion of the foreground, which could be people or cars. Obviously, frame difference only gives us a rough idea of which regions may contain moving objects, but such a simple method can neither sperate the foreground from the background, nor tell us which image regions are moving regions. As a resul...
متن کاملFast Parallel Object Tracking
The task of object tracking is the following: given a video and an identified object (usually given by a bounding box in the first frame), track the position of the object over the frames of the video. Difficulties in this process include occlusion or changes in orientation. The algorithm by Grabner, Grabner, and Bischof [3] is robust against these changes by using a large number of “weak class...
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ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 1993
ISSN: 1474-6670
DOI: 10.1016/s1474-6670(17)49287-1