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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...
This paper describes a method for traffic signs detection, tracking and recognition. Color and shape are combined to detect signs. Hue and saturation are used to detect the red color of the sign. Circles are detected through the improved round-degree method of extracting area feature parameters. An improved Kalman filter is introduced to track multiple targets in the next frames. A feature extraction...
In this paper, we propose a new algorithm for optimally adapting ellipses outlining objects of interest in order to improve the performance of a colour based tracking approach for real video sequences. We present a Lagrangian based method to integrate a regularising component into the covariance matrix to be computed. Technically, we intend to reduce the residuals between the estimated probability...
Basically depends on colors-analysis-based edge tracking algorithm, we put forward a colors-analysis-based self-adaptive method to trace the edge of the image in the paper. The method aims at the characteristics of pellet images by combining the edge detection and edge points, under direction of circle figure knowledge, and achieves detected character points of image edges automatically. The experimental...
Level set tracking has been widely used for tracking contours of objects. However, traditional methods are sensitive to noise, partial occlusions, background disturbance and some other factors, especially there exist serious problems for non-rigid objects tracking. With respect to this point, we propose a level set-based tracking framework in which color and dynamical shape priors are fused together...
Traditional object tracking based on color histograms can only represent objects with rectangles or ellipses, thus having very limited ability to follow objects with complex shapes or with highly non-rigid motion. In addressing this problem, we formulate histogram-based tracking as a functional optimization problem based on Jesson-Shannon divergence that is bounded, symmetric and a true metric. Optimization...
In this paper, a novel multi-cue collaborative kernel tracking algorithm is proposed. A new constraint based on the property of cross ratio invariant enables tracking of objects insensitive to complex motions, including scale changes, rotation and especially views changes, without labeling and training. Meanwhile, invariant moments are introduced into the kernel based tracking method as the shape...
Robust and real time moving object tracking is a tricky job in computer vision problems. Particle filtering has been proven very successful for non-Gaussian and non-linear estimation problems. In this paper, we first try to develop a color based particle filter. In this approach, the object tracking system relies on the deterministic search of window, whose color content matches a reference histogram...
According to the different color information of the different component in Hue-Saturation-Intensity color model, combining and ameliorating several basal arithmetics, we present a new method based on both shape and color information of the moving object. Experiments show the effectivity and feasibility of the method. And it also shows good anti-jamming quality in all experiments. Though our method...
Complex motion makes consecutive frames experience dramatic change, and thus becomes a barrier to object-tracking. Three factors contribute to more complexity of motion: longer sampling period,an moving object with complex appearance and nonrestraint movement, occlusion, which causes mean shift algorithm losing its target due to too low a Bhattacharyya coefficient. To treat it, mean shift algorithm...
This article presents a laboratory computer vision system for vehicle detection and tracking. Vehicles are marked with colored circles, that are detected by the presented computer vision system. Detection of targets is performed by their shape using circular Hough transform. Once the locations of the targets are known, their colors are acquired. Tracking of the targets through video frames is then...
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