DocumentCode :
2214549
Title :
Image model based on salient regions and its applications
Author :
Wang, Surong ; Chia, Liang-Tien
Author_Institution :
Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore
fYear :
0
fDate :
0-0 0
Abstract :
Detection, representation, and training are the three main issues that need to be resolved in an object recognition or classification system. One possible method is using collection of regions to represent object categories where each region has a distinctive feature. In this paper we present a region-based image model which learn and classify objects by training the image model with variant of the objects within the same category. Each object category is represented by a constellation of representative parts. These regions are detected by salient region detector over suitable scales. The standard disjunction rule is applied to construct the image model. During the learning procedure the distance between any two regions is calculated and accumulated as a measure which is inversely proportional to the probability of a match. The regions with large distances are removed from the image model iteratively. Finally, a small set of regions is kept as the image model. This image model can be used to retrieve similar images or for object classification. Experimental results show the method is easy to calculate and efficient
Keywords :
image classification; image representation; object recognition; image model; image retrieval; object category; object classification; object recognition; salient region detector; standard disjunction rule; Airplanes; Application software; Computer networks; Image databases; Image retrieval; Layout; MPEG 7 Standard; Marketing and sales; Probability; Visual databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multi-Media Modelling Conference Proceedings, 2006 12th International
Conference_Location :
Beijing
Print_ISBN :
1-4244-0028-7
Type :
conf
DOI :
10.1109/MMMC.2006.1651311
Filename :
1651311
Link To Document :
بازگشت