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» Semantic kernel learning for interactive image retrieval
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CVPR
2011
IEEE
12 years 11 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
CIVR
2010
Springer
204views Image Analysis» more  CIVR 2010»
13 years 11 months ago
Utilizing related samples to learn complex queries in interactive concept-based video search
One of the main challenges in interactive concept-based video search is the insufficient relevant sample problem, especially for queries with complex semantics. To address this pr...
Jin Yuan, Zheng-Jun Zha, Zhengdong Zhao, Xiangdong...
MMS
2006
13 years 7 months ago
A probabilistic semantic model for image annotation and multi-modal image retrieval
This paper addresses automatic image annotation problem and its application to multi-modal image retrieval. The contribution of our work is three-fold. (1) We propose a probabilis...
Ruofei Zhang, Zhongfei (Mark) Zhang, Mingjing Li, ...
SAC
2002
ACM
13 years 7 months ago
Color patterns for pictorial content description
In this paper, we propose a new type of image feature, which consists of patterns of colors and intensities that capture the latent associations among images and primitive feature...
Daniela Stan, Ishwar K. Sethi
ICIP
2001
IEEE
14 years 9 months ago
Image retrieval with relevance feedback: from heuristic weight adjustment to optimal learning methods
Various relevance feedback algorithms have been proposed in recent years in the area of content-based image retrieval. This paper gives a brief review and analysis on existing tec...
Xiang Sean Zhou, Thomas S. Huang