Finding Pictures of Objects in Large Collections of Images
ECCV '96 Proceedings of the International Workshop on Object Representation in Computer Vision II
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Content based sub-image retrieval via hierarchical tree matching
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
An integrated content and metadata based retrieval system for art
IEEE Transactions on Image Processing
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This work presents a content-based image retrieval system of general purpose that deals with cluttered scenes containing a given query object. The system is flexible enough to handle with a single image of an object despite its rotation, translation and scale variations. The image content is divided in parts that are described with a combination of features based on geometrical and color properties. The idea behind the feature combination is to benefit from a fuzzy similarity computation that provides robustness and tolerance to the retrieval process. The features can be independently computed and the image parts can be easily indexed by using a table structure on every feature value. Finally a process inspired in the alignment strategies is used to check the coherence of the object parts found in a scene. Our work presents a system of easy implementation that uses an open set of features and can suit a wide variety of applications.