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Edge and surface are two fundamental visual elements of an object. The majority of existing object proposal approaches utilize edge or edge-like cues to rank candidates, while we consider that the surface cue containing the 3D characteristic of objects should be captured effectively for proposals, which has been rarely discussed before. In this paper, an object-level proposal model is presented, which...
Depth-Image-Based-Rendering (DIBR) is fundamental in free-viewpoint 3D video, which has been widely used to generate synthesized views from multi-view images. The majority of DIBR algorithms cause disoccluded regions, which are the areas invisible in original views but emerge in synthesized views. The quality of synthesized images is mainly contaminated by distortions in these disoccluded regions...
Given 3D outdoor scenes acquired by a LIDAR sensor, we address the problem of semantic segmentation of 3D point clouds involving simultaneously segmenting and classifying the data. The capability of semantic segmentation is essential for several applications, such as autonomous robot navigation and 3D reconstruction of point clouds. In this paper, we present a higher-order class-specific CRF model...
In Cognitive Radio systems, the performance of spectrum sensing will directly affect spectrum reallocation. Energy detection (ED) method is one of the most commonly used signal sensing methods in spectrum sensing, due to its low implementation complexity. ED can achieve a good detection performance when the noise variance is known. However in most cases, the noise variance is estimated. To reduce...
View level bit allocation is an fundamental optimization problem in multiview video plus depth (MVD) based 3D video coding (3DVC). In this paper, we propose a smooth view quality oriented view level bit allocation framework for MVD based 3DVC. The Cauchy-density based rate-distortion model of the texture video and depth map are employed to represent the rate distortion properties. The relationship...
To understand scenes and help autonomous robots and cars, researchers' attention is directed through the problem of classifying 3D point cloud. In this paper, we present a novel approach to semantically segment 3D point cloud of residential scenes captured by a lidar sensor. Our approach is based on a dual-scale analysis: a small-scale clustering and a large-scale grouping. Features used to train...
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