Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting Salient Curves from Images: An Analysis of the Saliency Network
International Journal of Computer Vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding salient regions in images: nonparametric clustering for image segmentation and grouping
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Evaluation of Interest Point Detectors
International Journal of Computer Vision - Special issue on a special section on visual surveillance
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Filter Image Browsing: Interactive Image Retrieval by Using Database Overviews
Multimedia Tools and Applications
Emergent Semantics through Interaction in Image Databases
IEEE Transactions on Knowledge and Data Engineering
Ontology-Based Photo Annotation
IEEE Intelligent Systems
Content-based trademark retrieval system using visually salient features
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Unsupervised Extraction of Salient Region-Descriptors for Content Based Image Retrieval
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
Segmentation of Salient Closed Contours from Real Images
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
| Hi-index | 0.00 |
Content-based image retrieval (CBIR) has been under investigation for a long time with many systems built to meet different application demands. However, in all systems, there is still a big gap between the user's expectation and the system's retrieval capabilities. Therefore, user interaction is an essential component of any CBIR system. Interaction up to now has mostly focused on global image features or similarities. We consider the interaction with salient details in the image i.e. points, lines, and regions. Interactive salient detail definition goes further than automatically summarizing the image into a set of salient details. We aim to dynamically update the user- and context-dependent definition of saliency based on relevance feedback from the user. In this paper, we propose an interaction framework for salient details from the perspective of the user.