Title :
Automatic view selection in multi-view object recognition
Author :
Abbasi, Sadegh ; Mokhtarian, Farzin
Author_Institution :
Centre for VisionSpeech & Signal Processing, Surrey Univ., Guildford, UK
Abstract :
We introduce a new method for automatic selection of optimal views in a shape-based method of multi-view 3D object representation and recognition. A 3D object is recognised by an optimum number of images taken from different views. The object boundary of each view is considered as a 2D shape and is represented by the locations of the maxima of its curvature scale space (CSS) image contours. An unknown object is then recognised by a single image taken from an arbitrary viewpoint. The method has been tested on a collection of 3D objects consisting of 15 aircraft of different shapes. Each object has been modelled using an optimised number of silhouette contours obtained from different view points. The results obtained show that robust and efficient 3D free form object recognition through multi-view representation can be achieved using the CSS representation even for large database retrieval applications
Keywords :
edge detection; image representation; image retrieval; object recognition; stereo image processing; visual databases; 2D shape; 3D object recognition; curvature scale space; image contours; image representation; image retrieval; multiple-view; silhouette; visual database; Automatic speech recognition; Cascading style sheets; Data mining; Image databases; Image recognition; Information retrieval; Object recognition; Shape; Signal processing; Speech processing;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.905266