Multimedia Systems - Special issue on content-based retrieval
The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance evaluation in content-based image retrieval: overview and proposals
Pattern Recognition Letters - Special issue on image/video indexing and retrieval
Performance characterisation in computer vision: statistics in testing and design
Imaging and vision systems
Empirical Evaluation Techniques in Computer Vision
Empirical Evaluation Techniques in Computer Vision
On Performance Characterization and Optimization for Image Retrieval
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Query-Dependent Performance Optimization for Vocabulary-Supported Image Retrieval
Proceedings of the 24th DAGM Symposium on Pattern Recognition
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
IEEE Transactions on Image Processing
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
Scene Retrieval of Natural Images
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Eva: an evaluation tool for comparing descriptors in content-based image retrieval tasks
Proceedings of the international conference on Multimedia information retrieval
Facial feature localization using weighted vector concentration approach
Image and Vision Computing
An effective image retrieval scheme using color, texture and shape features
Computer Standards & Interfaces
Aerial photo image retrieval using adaptive image classification
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Multimedia information retrieval based on pairwise comparison and its application to visual search
Multimedia Tools and Applications
Self organizing natural scene image retrieval
Expert Systems with Applications: An International Journal
A new content-based image retrieval technique using color and texture information
Computers and Electrical Engineering
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Performance evaluation of content-based image retrieval (CBIR) systems is an important but still unsolved problem. The reason for its importance is that only performance evaluation allows for comparison and integration of different CBIR systems. We propose an image retrieval system that splits the retrieval process into two stages. Users are querying the system through image description using a set of local semantic concepts and the size of the image area to be covered by the particular concept. In Stage I of the system, only small patches of the image are analyzed whereas in the second stage the patch information is processed and the relevant images are retrieved. In this two-stage retrieval system, the retrieval performance, that is precision and recall, can be modeled statistically. Based on the model, we develop closed-form expressions that allow for the prediction as well as the optimization of the retrieval performance. As shown through experiments, the retrieval precision can be increased by up to 55% and the retrieval recall by up to 25% depending on the user query.