An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Context-based vision system for place and object recognition
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Generic Object Recognition with Boosting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incremental learning of object detectors using a visual shape alphabet
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Scalable Recognition with a Vocabulary Tree
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Cognitive maps for mobile robots-an object based approach
Robotics and Autonomous Systems
A boundary-fragment-model for object detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
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Object recognition has been widely researched for several decades and in the recent years new methods capable of general object classification have appeared. However very few work has been done to adapt these methods to the challenges raised by mobile robotics. In this article we discuss the data sources (appearence information, temporal context, etc.) that such methods could use and we review several state of the art object recognition methods that build in one or more of these sources. Finally we run an object based robot localization experiment using an state of the art object recognition method and we show that good results are obtained even with a naïve place descriptor.