Shock Graphs and Shape Matching
International Journal of Computer Vision
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape Representation and Classification Using the Poisson Equation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape context and chamfer matching in cluttered scenes
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Toward automated generation of parametric BIMs based on hybrid video and laser scanning data
Advanced Engineering Informatics
Hi-index | 0.00 |
In this paper, a new method for the problem of shape representation and classification is proposed. In this method, we define a radius function on the contour of the shape which captures for each point of the boundary, attributes of its related internal part of the shape. We call these attributes as "depth" of the point. Depths of boundary points generate a descriptor sequence which represents the shape. Matching of sequences is performed using dynamic programming method and a distance measure is acquired. At last, different classes of shapes are classified using a hierarchical clustering method and the distance measure. The proposed method can analyze features of each part of the shape locally which this leads to the ability of part analysis and insensitivity to local deformations such as articulation, occlusion and missing parts. We show high efficiency of the proposed method by evaluating it for shape matching and classification of standard shape datasets.