| Abstract |
|
We introduce a new method for automatic selection of optimal views in a shape-based method of multi-view 3-D object representation and recognition. A 3-D object is recognized by an optimum number of images taken from different views. The object boundary of each view is considered as a 2-D shape and is represented by the locations of the maxima of its Curvature Scale Space (CSS) image contours. An unknown object is then recognized by a single image taken from an arbitrary viewpoint.The method has been tested on a collection of 3-D objects consisting of 15 aircrafts of different shapes. Each object has been modeled using an optimized number of silhouette contours obtained from different viewpoints. This number varies from 5 to 25 depending on the complexity of the object and the measure of expected accuracy.Around ten silhouette contours corresponding to random views are separately used as input for each object. Results indicated that robust and efficient 3-D free-form object recognition through multi-view representation could be achieved using the CSS representation even for large database retrieval applications.
|
 Additional Information
|
Citation:
Sadegh Abbasi, Farzin Mokhtarian,
"Automatic View Selection in Multi-View Object Recognition,"
icpr,
p. 1013,
15th International Conference on Pattern Recognition (ICPR'00) - Volume 1,
2000
|
