In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foregroun...
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It is well known that the backgrounds or the targets always change in real scenes, which weakens the effectiveness of classical tracking algorithms because of frequent model mismatches. In this paper, an object tracki...
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image segmentation is a fundamental process in many image, video, and computer vision applications. It is very essential and critical to imageprocessing and patternrecognition, and determines the quality of final re...
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ISBN:
(纸本)9781479927654
image segmentation is a fundamental process in many image, video, and computer vision applications. It is very essential and critical to imageprocessing and patternrecognition, and determines the quality of final result of analysis and recognition. This paper presents a semi-supervised strategy to deal with the issue of image segmentation. Each image is first segmented coarsely, and represented as a graph model. Then, a semi-supervised algorithm is utilized to estimate the relevance between labeled nodes and unlabeled nodes to construct a relevance matrix. Finally, a normalized cut criterion is utilized to segment images into meaningful units. The experimental results conducted on Berkeley image databases and MSRC image databases demonstrate the effectiveness of the proposed strategy.
The unscented Kalman filter is an effective nonlinear estimation method for nonlinear system. As we all know that, one of the basic assumptions of unscented Kalman filter implementation is that the measurement noise a...
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A contour segmentation algorithm is proposed based on GVF Snake model and Contourlet transform. Firstly, object contours of images can be obtained based on Contourlet Transform, and those contours will be identified a...
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Interior tomography is to reconstruct the interior region of interest (ROI) from the projection data just across the ROI. One kind of interior reconstruction methods is based on the inversion of truncated Hilbert tran...
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Interior tomography is to reconstruct the interior region of interest (ROI) from the projection data just across the ROI. One kind of interior reconstruction methods is based on the inversion of truncated Hilbert transform (THT) when there is a known sub-region inside ROI. However, the result via this method is usually to be degraded by noise in real data case. In this paper, we propose to incorporate the total variation (TV) minimization constraint into the THT-based interior tomography to improve the reconstruction quality. Therein, we first carry out projection-on-convex-sets (POCS) iteration on each chord, and then we perform a soft-threshold based TV minimization on the intermediate image. In order to validate the proposed method, we conduct both simulated and real data experiments. The results show that with TV constraint the proposed method can lead to better ROI with less noise.
In this paper, we describe a novel 3D shape retrieval method based on new features. The features are extracted for 3D points based on a 2D attribute space which consists of two bidirectional 3D shape attributes, one o...
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ISBN:
(纸本)9781479905607
In this paper, we describe a novel 3D shape retrieval method based on new features. The features are extracted for 3D points based on a 2D attribute space which consists of two bidirectional 3D shape attributes, one of which along the shape surface direction and the other along the shape content direction perpendicular to the former. We define this features as Point Bidirectional Features (PBFs), which can reflect not only the global shape but also the local content. For simplicity, we choose the geodesic distance (GD) and the shape diameter function (SDF) to construct PBFs. Given a database of 3D shapes and a query shape, the proposed retrieval method adopts a shape similarity measurement based on 3D points matching with PBFs to decide which is the most similar shape from the database. To reduce cost of computation and feature storage, a shape simplification algorithm is integrated into this method. Additionally, a simple but effective point correspondence mechanism with K-Nearest Neighbor (KNN) assignment is designed for this retrieval method. Experimental results demonstrate the effectiveness of the proposed features and method.
Level set method is convenient in image segmentation for the stabilization and *** filter is usually taken as a preprocess to reduce the influence of weak edges due to noises,but the disadvantage is obvious:blur fine ...
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Level set method is convenient in image segmentation for the stabilization and *** filter is usually taken as a preprocess to reduce the influence of weak edges due to noises,but the disadvantage is obvious:blur fine structures specially the important boundaries and lead to inaccurate segmentation *** paper introduces a robust method which filters the images with a Nonlinear Coherent Diffusion(NCD) to accelerate the evolution of level set in a spatially varying *** results show the performance of the proposed method in improving precision of segmentation.
Since fully automatic image segmentation on natural images is usually hard to provide guaranteed results, interactive scheme with a few simple user inputs becomes a good alternative. This paper presents a novel intera...
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Since fully automatic image segmentation on natural images is usually hard to provide guaranteed results, interactive scheme with a few simple user inputs becomes a good alternative. This paper presents a novel interactive method based on regional attacking and merging mechanism within a cellular automaton(CA) framework. With an attacking rule based on regions maximal similarity, the adjacent homogeneous regions that are initialized by pre-segmentation are automatically merged and labeled, the users only need to indicate the object and background regions with rough markers. The whole process needn't set any similarity threshold in advance and the desired contours are effectively extracted by labeling all the non-marker regions as either background or object. Extensive experiments are performed and the results show that the proposed scheme can reliably extract the object contours from the complex background.
Road sign detection plays an important role in driver assistance system. However, it faces problems of high computational cost and low contrast in video sequences. In this paper, we propose a two-level hierarchical al...
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ISBN:
(纸本)9781479923427
Road sign detection plays an important role in driver assistance system. However, it faces problems of high computational cost and low contrast in video sequences. In this paper, we propose a two-level hierarchical algorithm which addresses these problems by making better use of the color and shape information of road signs. In order to solve the problem of low image contrast, we propose to improve the color contrast using our algorithm based on visual saliency. In order to reduce the high computational cost, an improved radial symmetry transform (IRST) is developed for grouping feature points on the basis of their underlying symmetry in an image. Experimental results show that our methods are robust to a broad range of lighting conditions and efficient enough for real-time applications.
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