ACM SIGGRAPH 2005 Papers
Selecting Distinctive 3D Shape Descriptors for Similarity Retrieval
SMI '06 Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006
Spectral surface quadrangulation
ACM SIGGRAPH 2006 Papers
Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
SGP '05 Proceedings of the third Eurographics symposium on Geometry processing
Surface matching with salient keypoints in geodesic scale space
Computer Animation and Virtual Worlds - CASA'2008 Special Issue
Salient spectral geometric features for shape matching and retrieval
The Visual Computer: International Journal of Computer Graphics
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Shape analysis using the auto diffusion function
SGP '09 Proceedings of the Symposium on Geometry Processing
IEEE Transactions on Image Processing
International Journal of Computer Vision
ACM SIGGRAPH 2010 Courses
Heat kernel smoothing using laplace-beltrami eigenfunctions
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
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
Schelling points on 3D surface meshes
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
New spectral methods for ratio cut partitioning and clustering
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Evaluation of 3D interest point detection techniques via human-generated ground truth
The Visual Computer: International Journal of Computer Graphics - 3DOR 2011
Visual Saliency Based on Scale-Space Analysis in the Frequency Domain
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mesh saliency via spectral processing
ACM Transactions on Graphics (TOG)
Hi-index | 0.00 |
This paper presents a method for detecting points of interest on 3D meshes. It comprises two major stages. In the first, we capture saliency in the spectral domain by detecting spectral irregularities of a mesh. Such saliency corresponds to the interesting portions of surface in the spatial domain. In the second stage, to transfer saliency information from the spectral domain to the spatial domain, we rely on spectral irregularity diffusion (SID) based on heat diffusion. SID captures not only the information about neighbourhoods of a given point in a multiscale manner, but also cues related to the global structure of a shape. It thus preserves information about both local and global saliency. We finally extract points of interest by looking for global and local maxima of the saliency map. We demonstrate the advantages of our proposed method using both visual and quantitative comparisons based on a publicly available benchmark.