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In this paper, we propose an unsupervised bottom-up method which formulates salient object detection problem as finding salient vertices of a graph. Global contrast is extracted in a novel graph-based framework to determine localization of salient objects. Saliency values are assigned to regions in terms of nodes degrees on graph. The proposed method has been applied on SED2 dataset. The qualitative...
This paper is concerned with the problem of keyframe detection in appearance-based visual SLAM. Appearance SLAM models a robot's environment topologically by a graph whose nodes represent strategically interesting places that have been visited by the robot and whose arcs represent spatial connectivity between these places. Specifically, we discuss and compare various methods for identifying the next...
Object localization in an image is usually handled by searching for an optimal subwindow that tightly covers the object of interest. However, the subwindows considered in previous work are limited to rectangles or other specified, simple shapes. With such specified shapes, no subwindow can cover the object of interest tightly. As a result, the desired subwindow around the object of interest may not...
In this paper, we address the problem of automatic pre-segmentation for object detection and recognition in remote sensing image processing. It plays an important role in reducing computational burden and increasing efficiency for further image processing and analysis. A visual-attention based saliency computation approach is introduced to select the perceptually salient and highly informative regions...
This work deals with the problem of automatic temporal segmentation of a video into elementary semantic units known as scenes. Its novelty lies in the use of high-level audio information in the form of audio events for the improvement of scene segmentation performance. More specifically, the proposed technique is built upon a recently proposed audio-visual scene segmentation approach that involves...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and to be matched may be very large, or even redundantly represent the shape information present. Since selective attention is a basic mechanism of the visual system, we explore whether there is a subset of salient points that...
Recent researches show that the benefits of image segmentation have been exploited in object categorization and recognition approaches. In most of these works, objects are segmented from the background around to increase recognition accuracy. However, it is generally hard to find a segmentation that captures all correct object boundaries in images of real world scene. So some researches begin to choose...
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