The analysis and applications of adaptive-binning color histograms
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Salient spectral geometric features for shape matching and retrieval
The Visual Computer: International Journal of Computer Graphics
Protrusion-oriented 3D mesh segmentation
The Visual Computer: International Journal of Computer Graphics
Contextual Part Analogies in 3D Objects
International Journal of Computer Vision
Harris 3D: a robust extension of the Harris operator for interest point detection on 3D meshes
The Visual Computer: International Journal of Computer Graphics - Special Issue on 3DOR 2010
Visual vocabulary signature for 3D object retrieval and partial matching
EG 3DOR'09 Proceedings of the 2nd Eurographics conference on 3D Object Retrieval
SHREC'10 track: feature detection and description
EG 3DOR'10 Proceedings of the 3rd Eurographics conference on 3D Object Retrieval
Evaluation of 3D interest point detection techniques
EG 3DOR'11 Proceedings of the 4th Eurographics conference on 3D Object Retrieval
Key-components: detection of salient regions on 3D meshes
The Visual Computer: International Journal of Computer Graphics
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In this paper, we present a method to detect stable components on 3D meshes. A component is a region on the mesh which contains discriminative local features. Our goal is to represent a 3D mesh with a set of regions, which we called key-components, that characterize the represented object and therefore, they could be used for effective matching and recognition. As key-components are features in coarse scales, they are less sensitive to mesh deformations such as noise. In addition, the number of key-components is low compared to other local representations such as keypoints, allowing us to use them in efficient subsequent tasks. An desirable characteristic of a decomposition is that the components should be repeatable regardless shape transformations. We show in the experiments that the key-components are repeatable under several transformations using the SHREC'2010 feature detection benchmark.