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Recent advances in the joint processing of images have certainly shown its advantages over the individual processing. Different from the existing works geared towards co-segmentation or co-localization, in this paper, we explore a new joint processing topic: co-skeletonization, which is defined as joint skeleton extraction of common objects in a set of semantically similar images. Object skeletonization...
Despite recent advances in joint processing of images, sometimes it may not be as effective as single image processing for object discovery problems. In this paper while aiming for common object detection, we attempt to address this problem by proposing a novel QCCE: Quality Constrained Co-saliency Estimation method. The approach here is to iteratively update the saliency maps through co-saliency...
Most existing high-performance co-segmentation algorithms are usually complicated due to the way of co-labelling a set of images and the requirement to handle quite a few parameters for effective co-segmentation. In this paper, instead of relying on the complex process of co-labelling multiple images, we perform segmentation on individual images but based on a combined saliency map that is obtained...
Localizing, recognizing, and segmenting multiple foreground objects jointly from a general user's photo stream that records a specific event is an important task with many useful applications. As argued in recent Multiple Foreground Cosegmentation (MFC) work by Kim and Xing, this task is very challenging in that it contrasts substantially from the classical cosegmentation problem, and aims to parse...
Kinect depth maps often contain missing data, or "holes", for various reasons. Most existing Kinect-related research treat these holes as artifacts and try to minimize them as much as possible. In this paper, we advocate a totally different idea - turning Kinect holes into useful information. In particular, we are interested in the unique type of holes that are caused by occlusion of the...
Though quite a few image segmentation benchmark datasets have been constructed, there is no suitable benchmark for semantic image segmentation. In this paper, we construct a benchmark for such a purpose, where the ground-truths are generated by leveraging the existing fine granular ground-truths in Berkeley Segmentation Dataset (BSD) as well as using an interactive segmentation tool for new images...
Given any image input by users, how to automatically cutout the object-of-interest is a challenging problem due to lack of information of the object-of-interest and the background. Saliency detection techniques are able to provide some rough information about object-of-interest since they highlight high-contrast or high attention regions or pixels. However, the generated saliency map is often noisy...
The state-of-the-art interactive image segmentation algorithms are often not able to produce accurate segmentation results with one-shot user input, and they frequently rely on laborious user editing to refine the segmentation boundary. In this paper, we propose a constrained active contour method for boundary refinement, which can be used to improve the segmentation results of many existing region-based...
Seeded image segmentation is a popular type of supervised image segmentation in computer vision and image processing. Previous methods of seeded image segmentation treat the image as a weighted graph and minimize an energy function on the graph to produce a segmentation. In this paper, we propose to conduct the seeded image segmentation according to the result of a heat diffusion process in which...
Playfield detection is an important task in sports video content analysis, as it provides the ground for further operations such as object detection, object tracking or semantic event highlight and summarization. Traditional approaches of playfield detection usually rely on the homogeneity cue of the field pixels' color to separate it from other areas within the image frame. Although encouraging results...
Dissolves are the basic artificial effects of gradual transitions in video sequences, which are widely used in TV programs and movies. Through dissolve detection, interesting and important video temporal segments can be easily located and indexed for various applications. In this paper, we present an effective dissolve detection algorithm, which takes into account the dissolve properties in both temporal...
For network-based graphics applications, a key challenge is how to efficiently transmit complex three-dimensional (3D) models over bandwidth-limited communication channels such as wireless links. Most existing 3D mesh coding algorithms do not consider the view-dependent rendering issue, and therefore result in transmitting unnecessary portions of 3D mesh models which leads to the waste in precious...
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