Robust motion estimation using spatial Gabor-like filters
Signal Processing
Invariant Feature Extraction and Object Shape Matching Using Gabor Filtering
VISUAL '02 Proceedings of the 5th International Conference on Recent Advances in Visual Information Systems
Image Reconstruction from Gabor Magnitudes
BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Multi-class relevance feedback content-based image retrieval
Computer Vision and Image Understanding
Image Representation by Complex Cell Responses
Neural Computation
Evolutionary feature synthesis for facial expression recognition
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
Fast hardware implementation of Gabor filter based motion estimation
Integrated Computer-Aided Engineering
A stream system-on-chip architecture for high speed target recognition based on biologic vision
ACSAC'07 Proceedings of the 12th Asia-Pacific conference on Advances in Computer Systems Architecture
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This paper presents a model-based object recognition approach that uses a Gabor wavelet representation. The key idea is to use magnitude, phase, and frequency measures of the Gabor wavelet representation in an innovative flexible matching approach that can provide robust recognition. The Gabor grid, a topology-preserving map, efficiently encodes both signal energy and structural information of an object in a sparse multiresolution representation. The Gabor grid subsamples the Gabor wavelet decomposition of an object model and is deformed to allow the indexed object model match with similar representation obtained using image data. Flexible matching between the model and the image minimizes a cost function based on local similarity and geometric distortion of the Gabor grid. Grid erosion and repairing is performed whenever a collapsed grid, due to object occlusion, is detected. The results on infrared imagery are presented, where objects undergo rotation, translation, scale, occlusion, and aspect variations under changing environmental conditions