Unsupervised Learning of Finite Mixture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simple Gabor feature space for invariant object recognition
Pattern Recognition Letters
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
The Representation and Matching of Pictorial Structures
IEEE Transactions on Computers
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Object class detection using local image features and point pattern matching constellation search
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
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Several novel methods based on locally extracted object features and spatial constellation models have recently been introduced for invariant object detection and recognition. The accuracy and reliability of the methods depend on the success of both tasks: evidence extraction and spatial constellation model search. In this study an accurate and efficient method for evidence extraction is introduced. The proposed method is based on simple Gabor features and their statistical ranking.