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The Hough transform is a feature extraction technique used in image analysis, computer vision and digital image processing. Usually it is used for detecting straight lines and curves. The purpose of the technique is to find imperfect instances of patterns within a certain class of shapes by a voting procedure. An improved Hough transform is proposed by using interval arithmetics in the accumulation...
We present a method for object tracking over time sequence imagery. The image plane is represented with a 4-connected planar graph where vertices are associated with pixels. On each image, the outer contour of the object is localized by finding the optimal cycle in the graph such that a cost function based on temporal, appearance and shape priors is minimized. Our contribution is the particle filtering-based...
Identifying moving objects in video sequence is fundamental and important task in visual tracking systems and computer vision applications. Background removal algorithms are usually used to separate the foreground from the background. Despite the existence of many background removal algorithms, they didn't solve some problems such as cast shadows, highlighting and ghost effect. In this paper we propose,...
In this paper, we propose a novel approach that combines particle filter tracking and 3D graph cut based segmentation to achieve silhouette tracking against drastic scale change and occlusion. The segmentation module offers particle filter tracking procedure the target shape information to compensate spatial information loss in the histogram based particle filter tracking process. Meanwhile, particle...
In this paper we address the problem of recovering object contour in infrared video sequences using active contours and level set methods. We propose an approach for variational segmentation of infrared images containing non-rigid, moving objects. The local regions-of-interest (ROIs) are identified firstly using statistical background-subtraction method. While the initialization of background model...
The current methods of mobile target detection of video sequences have shortcomings such as poor disturbance-resistance and robustness. To solve this problem, an modified GVF Snake algorithm was presented, new gradient vector field was founded which took full advantage of image gradient information, between-frame motion information and grey-level information of neighbor pixels. Simulation result indicates...
Object recognition and classification in a multi-environment is an important part of machine vision. The goal of this paper is to build a system that classifies the objects of interest plane and helicopter. This paper addresses the issues to classify objects by combining pose and viewpoint invariant to certain extend. The threshold technique with background subtraction is used to segment the background...
This paper proposes a novel detection method of rotational and divergent structures in still images based on Helmholtz decomposition. These structures are mathematical features in vector analysis. Traditionally, some detection methods of these structures in image sequences have been proposed. By using the Helmholtz decomposition, which can decompose flows into rotational and divergent components,...
The automatic reconstruction of 3D models from image sequences is still a very active field of research. All existing methods are designed for a given camera model, and a new (and ambitious) challenge is 3D modeling with a method which is exploitable for any kind of camera. A similar approach was recently suggested for structure-from-motion thanks to the use of generic camera models. In this paper,...
Sparse features have traditionally been tracked from frame to frame independently of one another. We propose a framework in which features are tracked jointly. Combining ideas from Lucas-Kanade and Horn-Schunck, the estimated motion of a feature is influenced by the estimated motion of neighboring features. The approach also handles the problem of tracking edges in a unified way by estimating motion...
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