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논문 기본정보
A Salient Based Bag of Visual Word Model (SBBoVW): Improvements toward Difficult Object Recognition and Object Location in Image Retrieval
논문 개요
| 기관명 | NDSL |
|---|---|
| 저널명 | KSII Transactions on internet and information systems : TIIS |
| ISSN | ,1976-7277 |
| ISBN |
논문저자 및 소속기관 정보
| 저자(한글) | Mansourian, Leila,Abdullah, Muhamad Taufik,Abdullah, Lilli Nurliyana,Azman, Azreen,Mustaffa, Mas Rina |
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| 저자(영문) | |
| 소속기관 | |
| 소속기관(영문) | |
| 출판인 | |
| 간행물 번호 | |
| 발행연도 | 2016-01-01 |
| 초록 | Object recognition and object location have always drawn much interest. Also, recently various computational models have been designed. One of the big issues in this domain is the lack of an appropriate model for extracting important part of the picture and estimating the object place in the same environments that caused low accuracy. To solve this problem, a new Salient Based Bag of Visual Word (SBBoVW) model for object recognition and object location estimation is presented. Contributions lied in the present study are two-fold. One is to introduce a new approach, which is a Salient Based Bag of Visual Word model (SBBoVW) to recognize difficult objects that have had low accuracy in previous methods. This method integrates SIFT features of the original and salient parts of pictures and fuses them together to generate better codebooks using bag of visual word method. The second contribution is to introduce a new algorithm for finding object place based on the salient map automatically. The performance evaluation on several data sets proves that the new approach outperforms other state-of-the-arts. |
| 원문URL | http://click.ndsl.kr/servlet/OpenAPIDetailView?keyValue=03553784&target=NART&cn=JAKO201616534187600 |
| 첨부파일 |
추가정보
| 과학기술표준분류 | |
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| ICT 기술분류 | |
| DDC 분류 | |
| 주제어 (키워드) | saliency map,SIFT feature,Bag of Visual Words model (BoVW),image retrieval,object recognition,and object location |