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Convolutional neural networks showed the ability in stereo matching cost learning. Recent approaches learned parameters from public datasets that have ground truth disparity maps. Due to the difficulty of labeling ground truth depth, usable data for system training is rather limited, making it difficult to apply the system to real applications. In this paper, we present a framework for learning stereo...
A hybrid clustering approach is proposed for processing image-like data such as plots in flow cytometry. Clustering or partitioning data into relatively homogeneous and coherent subpopulations can be an effective pre-processing method to achieve data analysis tasks such as pattern recognition and classification. Our method uses a graph to model the initial manual partition of the dataset. Based on...
Previous polarimetric synthetic aperture radar (PolSAR) images change detection methods are generally undertaken in the pixel scale, resulting in overlooking the semantic information. To solve this problem, this paper presents a superpixel-based PolSAR images change detection methods. Different from some previous methods, an improved SLIC superpixel segmentation method is introduced in polarimetric...
The problem of hot bursty topic detection in user generated texts deserves great attentions with the proliferation of Internet technologies. However, traditional document clustering and probabilistic topic models that were developed for formal news articles are less effective for informal user-generated corpora. In this paper, we provide a graph-based perspective that well reflects the latent pattern...
We propose a cross-trees structure to perform the non-local cost aggregation for dense stereo matching. The cross-trees structure consists of a horizontal-tree and a vertical-tree. Compared to other spanning trees, the significant superiority of the cross-trees is that the trees' constructions are efficient and independent on any local or global property. Moreover, the trees are exactly unique. By...
Atmospheric turbulence affects the imaging system at a long distance, which causes time-varying blur. Although the blur kernel is unknown, we propose an algorithm to estimate Optical Transfer Function (OTF) for long-exposure atmospheric turbulence blurred images. In this paper we present a novel image prior-isolate edges prior to predict a sharp ‘vision’ of degraded image edges, and utilize the two...
High-Efficiency Video Coding (HEVC) is the newest video coding standard which can significantly reduce the bit rate by 50% compared with existing standards. The key features and new tools in HEVC are designed for natural video sequences captured by a real camera. Different from natural videos, screen content contain much more edges in text and icon regions. The current video coding standards may blur...
In this paper, an effective constraint is proposed to leverage the stereo matching in early vision literature. Firstly, some particular edges are extracted to compose the new smooth constraint by categorizing the color edges into different groups. Then the optimal support windows can be established based on the proposed constraint. Finally, the disparity map would be estimated by using match propagation...
We propose a novel method on stereo matching based on the Global Edge Constraint (GEC) and Graph Cuts. Firstly, the GEC composed of particular image edges is employed to generate the initial disparity maps. And then the reliable disparity maps consistent with the observed data are extracted to construct the data term of the energy function. Finally, we incorporate the GEC as a soft constraint into...
We present a novel method on dense stereo matching; both high accuracy results and a handling of occlusions can be achieved with the edge constraint we prove in this paper. Though a lot of efforts had been made to solve the problems such as occlusions and disparity discontinuities, dense stereo matching is still very challenging in the field of stereo vision. Variable window methods seem to be a good...
Under-segmentation of an image with multiple objects is a common problem in image segmentation algorithms. This paper presents a novel approach for the splitting of clumps formed by multiple objects due to under-segmentation. The algorithm includes two steps: finding a pair of points for clump splitting, and joining the pair of selected points. In the first step, a pair of points for splitting is...
In this paper, we present a new automatic video object segmentation algorithm. The process of the algorithm can be divided into three parts: motion detection, spatial segmentation and object tracking, which integrates the spatial and temporal information of the video. The algorithm can extract the object of the video automatically. It is also applicable to videos with faster moving object and complex...
This paper presents a novel automatic 3D hybrid segmentation approach based on free-form deformation. The algorithms incorporate boosting and deformation gradients to achieve reliable liver segmentation of Computed Tomography (CT) scans. A free-form deformable model is deformed under the forces originating from boosting and deformation gradients. The basic idea of the scheme is to combine information...
At present, there are two main types for medical CT image surface reconstruction: one is way of the slice contour, the other is voxel reconstruction, the former method is simple, easy for calculation and much classical computer graphics techniques can be used, the latter is related to complex computing. In this paper, image contours are extracted by active contour model, simplified by DP algorithm...
This paper presents a novel gradient vector flow calculation method and introduces the center position of initial contour line to segment target exactly. The method utilizes the center position of initial contour line and image features to calculate external energy; the contour line can search for and estimate the real edge no matter where the center position of initial contour line is. Experimental...
This paper deals with the edge linking problem. We propose two improvements to existing algorithms. First we propose the use of an application-specific local neighborhood within which to compute edge direction in order to improve the accuracy of the edge direction. Second, we propose the use of geodesic distance for measuring the proximity between two candidate edge points to be linked, so that the...
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