نتایج جستجو برای: Keywords kernel based object tracking
تعداد نتایج: 4662141 فیلتر نتایج به سال:
Abstract In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...
target tracking is the tracking of an object in an image sequence. target tracking in image sequence consists of two different parts: 1- moving target detection 2- tracking of moving target. in some of the tracking algorithms these two parts are combined as a single algorithm. the main goal in this thesis is to provide a new framework for effective tracking of different kinds of moving target...
A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem can be fo...
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...
Object tracking is a process of segmenting a region of interest from a video scene and keeping track of its motion, position and occlusion. The tracking is performed by monitoring objects’ spatial and temporal changes during a video sequence, including its presence, position, size, shape, etc. Object tracking is used in several applications such as video surveillance, robot vision, traffic moni...
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...
The mean shift algorithm is one of the popular methods in visual tracking for non-rigid moving targets. Basically, it is able to locate repeatedly the central mode of a desirable target. Object representation in mean shift algorithm is based on its feature histogram within a non-oriented individual kernel mask. Truly, adjusting of the kernel scale is the most critical challenge in this method. ...
Tracking of multiple objects is an important application in AI City geared towards solving salient problems related to safety and congestion in an urban environment. Frequent occlusion in traffic surveillance has been a major problem in this research field. In this challenge, we propose a model-based vehicle localization method, which builds a kernel at each patch of the 3D deformable vehicle m...
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