Scale-Based Description and Recognition of Planar Curves and Two-Dimensional Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Two-dimensional, model-based, boundary matching using footprints
International Journal of Robotics Research
Index-based object recognition in pictorial data management
Computer Vision, Graphics, and Image Processing
Structural Indexing: Efficient 3-D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
International Journal of Computer Vision
Structural Indexing: Efficient 2D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
A hierarchical approach to efficient curvilinear object searching
Computer Vision and Image Understanding
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape representation and recognition from multiscale curvature
Computer Vision and Image Understanding
Model-based 3D object recognition using Bayesian indexing
Computer Vision and Image Understanding
Extended attributed string matching for shape recognition
Computer Vision and Image Understanding
3D free-form object recognition using indexing by contour features
Computer Vision and Image Understanding
Structural shape indexing with feature generation models
Computer Vision and Image Understanding
Indexing without Invariants in 3D Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multidimensional Indexing for Recognizing Visual Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modal Matching for Correspondence and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Shape Retrieval Using Term Frequency Vectors
CBAIVL '99 Proceedings of the IEEE Workshop on Content-Based Access of Image and Video Libraries
Indexing pictorial documents by their content: a survey of current techniques
Image and Vision Computing
Fast correspondence-based system for shape retrieval
Pattern Recognition Letters
Knowledge-based part correspondence
Pattern Recognition
Decomposition of two-dimensional shapes for efficient retrieval
Image and Vision Computing
Comparison of detailed descriptors for noisy silhouettes
Machine Graphics & Vision International Journal
LWDOS: language for writing descriptors of outline shapes
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
On the convergence of planar curves under smoothing
IEEE Transactions on Image Processing
Minimizing the search space for shape retrieval algorithms
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
| Hi-index | 0.00 |
Similarity-based retrieval from databases of isolated visual shapes has become an important information retrieval problem. The goal of the current work is to achieve high retrieval speed with reasonable retrieval effectiveness, and support for partial and occluded shape queries. In the proposed method, histograms of local shape parts are coded as index vectors. To increase retrieval accuracy, a rich set of parts at all scales of the shape is used; specifically, the parts are defined as connected sequences of regions in curvature scale space. To increase efficiency, structural indexing is used to compare the index vectors of the query and database shapes. In experimental evaluations, the method retrieved at least one similar shape in the top three retrieved items 99-100% of the time, depending on the database. Average retrieval times ranged from 0.7 ms on a 131-shape database to 7 ms on a 1310-shape database. The method is thus suitable for fast, approximate shape retrieval in comparison with more accurate but more costly structural matching.