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Self-Organising Maps (SOMs) can be used in implementing a powerful relevance feedback mechanism for Content-Based Image Retrieval (CBIR). This paper introduces the PicSOM CBIR system, and describes the use of SOMs as a relevance feedback technique in it. The technique is based on the SOM's inherent property of topology-preserving mapping from a high-dimensional feature space to a two-dimensional grid of artificial neurons. On this grid similar images are mapped in nearby locations. As image similarity must, in unannotated databases, be based on low-level visual features, the similarity of images is dependent on the feature extraction scheme used. Therefore, in PicSOM there exists a separate tree-structured SOM for each different feature type. The incorporation of the relevance feedback and the combination of the outputs from the SOMs are performed as two successive processing steps. The proposed relevance feedback technique is described, analysed qualitatively, and visualised in the paper. Also, its performance is compared with a reference method.

We have designed and evaluated a novel multiplayer game system using just one top-view camera. With the proposed system, player avatar movement can be directly mapped to the physical movement of the player, accompanied by additional hand gestures triggering more complex actions. This article presents a study of the concepts of body-driven multiplayer games using the proposed system. We have created four different test games using human-centered design (HCD). We describe both the computer vision- based implementation and the lessons we learned about designing effective content for interactive body-driven multiplayer games.

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Summary. We have developed a method that utilizes hypertext link information in image retrieval from the World Wide Web. The basis of the method consists of a set of basic relations that can take place between two images in the Web. Our method uses the SHA-1 message digest algorithm for dimension reduction by random mapping. The Web link features have then been used in creating a SelfOrganizing Map of images in the Web. The method has been effectively tested with our PicSOM content-based image retrieval system using a Web image database containing over a million images. The method can as such be used also in other Web applications not related to content-based image retrieval.