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Most video processing applications require object tracking as it is the base operation for real-time implementations such as surveillance, monitoring and video compression. Therefore, accurate tracking of an object under varying scene conditions is crucial for robustness. It is well known that illumination variations on the observed scene and target are an obstacle against robust object tracking causing...
The paper presents a novel multi-factorial approach for robust real-time object tracking. The target object is modeled using joint features of color (Intensity) histogram bins, texture, shape. In subsequent frames of a video, target localization is done by generating a confidence-map (a binary image) which discriminates foreground and background using K-means clustering algorithm. Random samples (sample...
Tracking multiple objects in surveillance scenarios involves considerable difficulty because of occlusions. We report a novel tracker - based on reliability tracking - that demonstrates superior performance under high degrees of occlusion. In our method, distinguishable features between the target and non-target are represented as the object's reliability. When the selected features are no longer...
Object tracking based on color feature often fails in a complex background. To deal with this problem, a particle filtering object tracking approach is proposed in this paper based on local binary pattern and color feature. Color histogram is the global description of targets in color image, while local binary pattern texture contains information of neighbor region texture in gray image. These two...
Radio frequency identification (RFID) applications set to play an essential role in object tracking and supply chain management systems. In future RFID technologies are expected that every major retailer will use RFID systems to track the movement of products from suppliers to warehouses, transportation and distribution. The volume of information generated by such systems is enormous. Despite all...
In this paper, an algorithm for tracking multiple rigid and non-rigid objects in conditions of occlusion is presented. The proposed method is based on a scalable and adaptive model based on joint information of color and shape. Through a GHT (generalized Hough transform) based voting method the center of mass of each object can be determined in real time with a good degree of precision. Quantitative...
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