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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...
Aiming at the difficulties of detecting and tracking ground targets, it puts forward a universal detecting and tracking algorithm of ground target based on the analysis and comparison of current detecting and tracking algorithms. Firstly it adopts inter-frame differencing algorithm and morphological filter algorithm to detect the potential targets. Then calculate the accurate position of targets based...
We propose a novel object tracking algorithm based on modeling the target appearance in a joint space. In contrast with traditional histogram-based trackers which discard all spatial information, the joint space takes both the photometric and spatial information into account. Within this joint space, the target is modeled in a Gaussian mixtures manner where a richer description of the target is captured...
Moving object tracking has received much interest in the field of computer vision due to the increasing need for automated video analysis. Particles Filter is a very promising object tracking method since it is suitable for non-linear and/or non-Gaussian applications. Most particle filter applies color information in target model which might fail in the presence of similar colored objects in the scene...
Omni-directional vision (omni vision) has been used in many fields because of its advantage of extremely wide view; one way to establish omni vision system is using fisheye lens. Target recognition and tracking is a tough task in computer vision, which is even more challenging in outdoor environment. In this paper, a recognition and tracking algorithm suitable for a natural target in outdoor environment...
Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to the object dynamics. The typical approach is to use a registration algorithm to compensate the camera motion. However, in situations involving several moving objects, and backgrounds highly affected by the aperture problem,...
Tracking 3d pose of a known object is one of the most important problems in computer vision. This paper proposes an appearance-based approach to this problem by combining the sparse template matching and the particle filter. Although the combination of them has already been discussed for 2d tracker, it has not been applied for efficient 3d tracking. This paper discusses an appearance-based tracker...
This paper proposes a visual tracking method based on dynamic extracting multi-features to realize the robust and accurately visual tracking. First select the features that can compensate for each other to set up the feature mode using histogram. Second build the correlation function of local background illumination varying and dynamic amending features of target. Dynamic adjust feature set according...
A 3D human tracking method based on particle filter is introduced in this paper. In this method, firstly the face area of the human is extracted based on a skin model and template matching with standard human face from recorded 2-D video images. Then 2-D face positions in the video images are converted to 3-D world coordinates through the calibration parameters. Finally these 3-D position estimates...
A novel strategy for the visual tracking and the information extracted problem is proposed which is for the case of maneuvering target. The strategy contains two methods. One is used to tracking, and the other one is used to extract the information of the vehicle. A non-linear estimation method using the particle filter to track objects is presented. During the tracking, a great deal of vehicle information...
This paper presents a particle filter based solution to the problem of detecting large frozen lumps in an image sequence, taken of the feed to a crusher, which is used for size reduction of oilsand ore. In this application, the objects of interest, i.e., large frozen lumps, are characterized by a high level of image noise, irregular shapes, and uneven and variable surface texture. In addition, more...
A robust approach to detection and tracking of multiple moving targets from a moving camera is presented. The main novelty of this approach is that objects are represented using efficient compact form of the colour correlogram. Like previous correlograms, this encodes both spatial pattern and appearance information about the target. However it is less complex to compute, making it applicable to real...
This paper describes an approach to tracking multiple independently moving objects observed from moving cameras. The method addresses difficulties typically associated with tracking, including changes in background, parallax in the scene, arbitrary camera motion, object occlusions, cross-overs, and appearance changes. Using a bottom up approach, independently moving objects are detected in images...
An appropriate measurement likelihood function is proposed from the measurement image model employed by most of the track-before-detect (TBD) approaches. Based on the likelihood function and a target motion model, we design an auxiliary particle filter-based Bayes multiframe method for detection and tracking a moving point target in infrared (IR) image sequences. Experimental results show its effectiveness...
Particle filtering is an efficient and successful technique for tracking 2D and 3D motion through an image. We present the enhanced tracking of two hands based on a statistical model using only a skin colour feature with particle filtering for gesture recognition. Our framework employs one particle filter per hand individually with the pixel-wise classification of the likelihood of the skin in the...
Region covariance descriptor recently proposed in has been approved robust and elegant to describe a region of interest which has been applied to visual tracking. By employing region covariance descriptor, the tracker efficiently fuses multiple features and modalities and has a capacity for comparing regions with different window sizes. Relying on the same principle of region covariance descriptor,...
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