Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Overview of the ImageCLEFphoto 2007 Photographic Retrieval Task
Advances in Multilingual and Multimodal Information Retrieval
Advances in Multilingual and Multimodal Information Retrieval
Towards Annotation-Based Query and Document Expansion for Image Retrieval
Advances in Multilingual and Multimodal Information Retrieval
Late fusion of heterogeneous methods for multimedia image retrieval
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
The segmented and annotated IAPR TC-12 benchmark
Computer Vision and Image Understanding
Overview of the ImageCLEFphoto 2008 photographic retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
The segmented and annotated IAPR TC-12 benchmark
Computer Vision and Image Understanding
Multimodal indexing based on semantic cohesion for image retrieval
Information Retrieval
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This paper describes experimental results of two approaches to multimedia image retrieval: annotation-based expansion and late fusion of mixed methods. The former formulation consists of expanding manual annotations with labels generated by automatic annotation methods. Experimental results show that the performance of text-based methods can be improved with this strategy, specially, for visual topics; motivating further research in several directions. The second approach consists of combining the outputs of diverse image retrieval models based on different information. Experimental results show that competitive performance, in both retrieval and results diversification, can be obtained with this simple strategy. It is interesting that, contrary to previous work, the best results of the fusion were obtained by assigning a high weight to visual methods. Furthermore, a probabilistic modeling approach to result-diversification is proposed; experimental results reveal that some modifications are needed to achieve satisfactory results with this method.