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Semantic event recognition based only on vision cues has had limited success on unconstrained still pictures. Metadata related to picture taking provides contextual cues independent of the image content and can be used to improve classification performance. With geotagged pictures, we investigate the novel use of satellite images (e.g., supplied by Google Earth??) corresponding to the GPS (global...
Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robust to dynamic changes and it should perform consistently when recognizing a room (for instance a corridor) in different...
Vision-based place recognition is a desirable feature for an autonomous mobile system. In order to work in realistic scenarios, visual recognition algorithms should be adaptive, i.e. should be able to learn from experience and adapt continuously to changes in the environment. This paper presents a discriminative incremental learning approach to place recognition. We use a recently introduced version...
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