ICA (Independent Component Analysis) is contrasted with PCA (Principal Component Analysis) in that ICA basis images are spatially localized, highlighting salient feature regions corresponding to eyes, eye brows, nose and lips. However, ICA basis images do not display perfectly local characteristic in the sense that pixels that do not belong to locally salient feature regions still have some wei...

Object-based visual attention has got more and more attention in image processing. A computational model of visual attention based on space and object is proposed in this study. Firstly spatial visual saliency of each pixel is calculated and edges of the input image are extracted. Salient edges are obtained according to the visual saliency of each edge. Secondly, a graph-based clustering proces...

We describe a method to automatically extract video objects, which are important for object-based indexing of videos in an MPEG-7 compliant video database system. Most of the existing salient object detection approaches detect visually conspicuous image structures, while our method aims to find regions that may be important for indexing in a video database system. Our method works on a shot bas...

Salient object detection aims to localize the most attractive objects within an image. For such a goal, accurately determining the saliency values of image regions and keeping the saliency consistency of interested objects are two key challenges. To tackle the issues, we first propose an adaptive combination method of incorporating texture with the dominant color, for enriching the informativen...

In this paper, we present a novel image retrieval technique based on salient regions that are invariant under viewpoint and illumination variations. The salient regions are detected according to local entropy and scale selection. The detected regions have very high repeatability under various viewpoint and illumination changes. We apply the invariant region detector on content-based image retri...

In this paper, a new method for saliency detection is proposed. Based on the defined features of the salient object, we solve the problem of saliency detection from three aspects. Firstly, from the view of global information, we partition the image into two clusters, namely, salient component and background component by employing Principal Component Analysis (PCA) and k-means clustering. Second...

Landmark-based navigation in unknown unstructured environments is far from solved. The bottleneck nowadays seems to be the fast detection of reliable visual references in the image stream as the robot moves. In our research, we have decoupled the navigation issues from this visual bottleneck, by first using artificial landmarks that could be easily detected and identified. Once we had a navigat...