Abstract--Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and dom...
Mohammad Mehdi Saboorian, Mansour Jamzad, Hamid R....
Image similarity search is a fundamental problem in computer vision. Efficient similarity search across large image databases depends critically on the availability of compact ima...
Kerui Min, Linjun Yang, John Wright, Lei Wu, Xian-...
If an image should be retrieved by its subregions from a large image database, an immense number of possible queries will appear. Therefore, the index which encodes the spatial in...
Abstract. Thanks to the recent explosive progress of WWW (WorldWide Web), we can easily access a large number of images from WWW. There are, however, no established methods to make...
Abstract. We propose a relevance feedback system for retrieving a mental face picture from a large image database. This scenario differs from standard image retrieval since the ta...
In this paper, a kernel-based method for multi-object retrieval in large image database is presented. First, our approach exploits a fuzzy region segmentation approach in order to...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...
In this paper, the matching of SIFT-like features [5] between images is studied. The goal is to decide which matches between descriptors of two datasets should be selected. This m...
We present a novel framework for intelligent search and retrieval by image content composition. Very different from the existing Query-by-Example paradigm, logical queries are exp...
We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we separate the salient obj...
Tie Liu, Jian Sun, Nanning Zheng, Xiaoou Tang, Heu...