The week's pick
Random Articles
Reseach Article
Picture Search in Client Expectation
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 117 - Number 20 |
| Year of Publication: 2015 |
| Authors: Sumit Suryakant Dhotre, Sathish Kumar Penchala |
10.5120/20671-3326
|
Sumit Suryakant Dhotre, Sathish Kumar Penchala . Picture Search in Client Expectation. International Journal of Computer Applications. 117, 20 ( May 2015), 15-18. DOI=10.5120/20671-3326
Abstract
Web-scale picture web crawlers (e. g. Google Picture Inquiry, Bing Picture Look) by and large rely on upon incorporating substance characteristics. It is troublesome for them to decipher customers' interest arrangement just by inquiry vital words and this prompts indeterminate and uproarious question things which are far from pleasant. It is basic to use visual information as a piece of solicitation to handle the unclearness in substance based picture recuperation. In this paper, we propose a novel Web picture chase approach. It just requires the customer to click on one request picture with the minimum effort and pictures from a pool recuperated by substance based chase are re-situated concentrated around both visual and printed substance. Our key duty is to catch the customers' interest point from this a solitary click request picture in four stages. (1) The inquiry picture is requested into one of the predefined adaptable weight classes, which mirror customers' chase suggestion at a coarse level. Inside every arrangement, a specific weight creation is used to join visual idiosyncrasies adaptable to this kind of pictures to better re-rank the substance based thing. (2) In light of the visual substance of the request picture picked by the customer and through picture gathering, inquiry definitive words are reached out to catch customer arrangement. (3) Extended enchantment words are used to develop the photo pool to contain more noteworthy pictures. (4) Extended watchwords are also used to develop the inquiry picture to distinctive positive visual cases from which new request specific visual and content based resemblance estimations are made sense of how to further upgrade substance based picture re-situating. Every one of these steps are modified without extra effort from the customer. This is discriminatingly crucial for any business electronic picture web searcher, where the customer interface must be enormously clear. Other than this key duty, an arrangement of visual contrivances which are both intense and capable in Web picture look for are sketched out.
References
- Xiaoou Tang, Fellow, IEEE, Ke Liu, Jingyu Cui, Student Member, IEEE, Fang Wen, Member, IEEE, and Xiaogang Wang, Member, "IntentSearch: Capturing User Intention for One-Click Internet Image Search" IEEE IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 34, NO. 7, JULY 2012
- F. Jing, C. Wang, Y. Yao, K. Deng, L. Zhang, and W. Ma, "Igroup: Web Image Search Results Clustering," Proc. 14th Ann. ACM Int?l Conf. Multimedia, 2006.
- J. Cui, F. Wen, and X. Tang, "Real Time Google and Live Image Search Re-Ranking," Proc. 16th ACM Int?l Conf. Multimedia, 2008.
- "Bing Image Search," http://www. bing. com/images, 2012.
- N. Ben-Haim, B. Babenko, and S. Belongie, "Improving Web- Based Image Search via Content Based Clustering," Proc. Int?l Workshop Semantic Learning Applications in Multimedia, 2006.
- http://en. wikipedia. org/wiki/Image_retrieval
- http://en. wikipedia. org/wiki/Content based_ image _retrieval 1339 International Journal of Engineering Research & Technology (IJERT)Vol. 2 Issue 4, April - 2013ISSN: 2278-0181
- A. Torralba, K. Murphy,W. Freeman, and M. Rubin, Contextbased vision system for place and object recognition, in Proc. Intl Conf. Computer Vision, 2003.
Index Terms
Keywords