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Block and sparse principal feature extraction-based rapid collaborative saliency detection method

A technology of sparse main features and detection methods, applied in the field of image processing, can solve problems such as limitations of collaborative saliency detection methods

Active Publication Date: 2015-03-04
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

However, as the image tends to be high-definition and the increase in the number of processed images brings about computer memory problems and time-consuming problems, it will undoubtedly bring huge limitations to the use of collaborative saliency detection methods in various applications.

Method used

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  • Block and sparse principal feature extraction-based rapid collaborative saliency detection method
  • Block and sparse principal feature extraction-based rapid collaborative saliency detection method
  • Block and sparse principal feature extraction-based rapid collaborative saliency detection method

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Embodiment

[0057] Example on Intel Core TM i3-3220 processor, 4G memory hardware environment. The operating system is Microsoft Windows 7, and the experimental simulation environment is Matlab 2008a. In order to verify the effectiveness of the above method, two standard data sets with artificial segmentation results, Co-saliency Pairs and CMU Cornell iCoseg, were used for experimental simulation, and the efficiency of displaying targets by examining the saliency map and the segmentation map based on the saliency map was evaluated. The performance of the method is analyzed and compared with the methods of Li (only two images are compared) and Fu with published experimental codes. Among them, the Co-saliency Pairs dataset contains 105 groups of 210 images, and the CMU Cornell iCoseg dataset contains 38 groups of 643 images (each target class contains 5 to 41 images). In order to facilitate calculation and processing, all input images are unified to a size of 200×200, and the image block ...

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Abstract

The invention relates to a block and sparse principal feature extraction-based rapid collaborative saliency detection method. The method sequentially includes the four steps of feature extraction of image blocks and original pixels, sparse principal feature extraction, clustering-based feature computation and collaborative saliency map generation. With the block and sparse principal feature extraction-based rapid collaborative saliency detection method adopted, limitations of application of existing collaborative saliency detection methods to various kinds of aspects which are brought by problems of memory occupation and time consumption which are further caused by ignoring of other saliency targets as well as increasingly high-definition images and the increase of the number of processing images in the prior art can be avoided.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a fast collaborative saliency detection method based on block and sparse main feature extraction. Background technique [0002] The motivation for the initial research on saliency detection was to predict human attention by simulating the human visual attention mechanism. In the past ten years, researchers have proposed many single-image saliency detection methods, and they have been widely used in salient object detection and segmentation, image retrieval and other applications. Co-saliency detection is to find common saliency targets from a group of images, which plays an important role in the research of target co-segmentation and co-recognition. It is a relatively new research field in saliency detection in recent years. Compared with the saliency detection method for a single image, the co-saliency detection method considers the correlation between different images...

Claims

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Application Information

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IPC IPC(8): G06K9/46
CPCG06V10/50G06V10/56
Inventor 周培云李静沈宁敏
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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