S. Servetto, Y. Rui, K. Ramchandran, and T. S. Huang. A region-based representation of images in MARS. Special Issue on multimedia Signal Processing, Journal on VLSI Signal Processing Systems, 20(2):137--150, October 1998. Home/Search Document Details and Download
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Image Background Search: Combining Object Detection.. - Srihari, Zhang, Rao (1999) (6 citations) (Correct)
....features is presented. This system may be useful in automatically generating albums from consumer photos. Keywords: Content Based Image Retrieval(CBIR) Averaged Precision and Recall(APR) Performance Area, Background Retrieval, Foreground Retrieval. 1. Introduction Traditional CBIR systems [2, 5, 1, 4] have achieved great success when dealing with pure scenery image data, but when images change from simple scenery to more semantically complex domain, such as images with human beings, the performance reduces significantly. The reason is: i) These systems do not differentiate the semantic ....
....do not differentiate the semantic foreground objects (e.g. human beings) from background scenery; ii) The matching schemes are based on certain primitive statistical information extracted from the combination of the foreground and the background scene. Examples of these systems may be found in [2, 6, 5, 1, 4]. To improve the performance of a CBIR system on semantically complex images, such as consumer photos, a more intelligent approach to picture classification and retrieval is necessary. In this paper, we first review the results of a traditional CBIR system which uses histogram vectors as ....
S. Servetto, Y. Rui, K. Ramchandran, and T. S. Huang. A region-based representation of images in mars. Special issue on multimedia Signal Processing, Journal on VLSI Signal Processing Systems, October 1998.
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S. Servetto, Y. Rui, K. Ramchandran, and T. S. Huang. A region-based representation of images in MARS. Special Issue on multimedia Signal Processing, Journal on VLSI Signal Processing Systems, 20(2):137--150, October 1998.
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