The photon mapping is one of the more widely used algorithms for rendering scenes with participating media. Currently, it suffers from two main problems: one is how to improve the rendering efficiency, and another is ...
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Many existing methods for salient object detection are performed by over-segmenting images into non-overlapping regions, which facilitate local/global color statistics for saliency computation. In this paper, we propo...
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Many existing methods for salient object detection are performed by over-segmenting images into non-overlapping regions, which facilitate local/global color statistics for saliency computation. In this paper, we propose a new approach: spectral salient object detection, which is benefited from selected attributes of normalized cut, enabling better retaining of holistic salient objects as comparing to conventionally employed pre-segmentation techniques. The proposed saliency detection method recursively bi-partitions regions that render the lowest cut cost in each iteration, resulting in binary spanning tree structure. Each segmented region is then evaluated under criterion that fit Gestalt laws and statistical prior. Final result is obtained by integrating multiple intermediate saliency maps. Experimental results on three benchmark datasets demonstrate the effectiveness of the proposed method against 13 state-of-the-art approaches to salient object detection.
Recently many graph-based salient region/object detection methods have been developed. They are rather effective for still images. However, little attention has been paid to salient region detection in videos. This pa...
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ISBN:
(纸本)9781479952106
Recently many graph-based salient region/object detection methods have been developed. They are rather effective for still images. However, little attention has been paid to salient region detection in videos. This paper addresses salient region detection in videos. A unified approach towards graph construction for salient object detection in videos is proposed. The proposed method combines static appearance and motion cues to construct graph, enabling a direct extension of original graph-based salient region detection to video processing. To maintain coherence in both intra- and inter-frames, a spatial-temporal smoothing operation is proposed on a structured graph derived from consecutive frames. The effectiveness of the proposed method is tested and validated using seven videos from two video datasets.
Foreground detection has always been of great concern in imageprocessing field. This paper focused on detecting moving objects in videos taken by moving cameras. The segmentation result is produced by a MRF-MAP label...
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A simple method is proposed to estimate the DOA using acoustic vector sensor in the presence of nonuniform noise. Algorithms mentioned in earlier works are shown to be susceptible to choice of weighted parameter. The ...
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In this paper, we investigate the Max-Cut problem and propose a probabilistic heuristic to address its classic and weighted version. Our approach is based on the Estimation of Distribution Algorithm (EDA) that creates...
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Graph models offer high representational power and useful structural cues. Unfortunately, tracking objects by matching graphs over time is in general NP-hard. Simple appearance-based trackers are able to find temporal...
Graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the...
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This paper proposes an approach for trajectory matching in video retrieval. Algorithm is consist of three parts. First, a terse trajectory contains most important temporal and spatial characters are abstracted. Then, ...
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In this paper, we take the advantages of color contrast and color distribution to get high quality saliency maps. The overall procedure flow of our unified framework contains superpixel pre-segmentation, color contras...
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