Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Labeling images with a computer game
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Improving efficiency and effectiveness of the image distortion model
Pattern Recognition Letters
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
The MIR flickr retrieval evaluation
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
PhotoSketch: a sketch based image query and compositing system
SIGGRAPH 2009: Talks
Retrieval by shape similarity with perceptual distance andeffective indexing
IEEE Transactions on Multimedia
Image retrieval at memory's edge: known image search based on user-drawn sketches
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
| Hi-index | 0.01 |
With the increasingly growing size of digital image collections, known image search is gaining more and more importance. Especially when the objects in such collections do not possess appropriate metadata (e.g., tags, annotations), content-based image retrieval (CBIR) is a promising approach. However, the application of CBIR to known item search usually suffers from the unavailability of query images that are good enough to express the user's information need. In order to improve this situation, we propose the QbS system which provides an approach to content-based search in large image collections based on user-drawn sketches. By exploiting novel devices for human-computer interaction like interactive paper, tablet PCs, or graphic tablets, users are able to draw a sketch that reflects their information need and start a content-based search using this sketch. The QbS system provides query support and offers several invariances that allow the user-generated sketch to slightly deviate from the searched image in terms of rotation, translation, relative size, and/or unknown objects in the background. To illustrate the benefits of the approach, we show search results from the evaluation of QbS on the basis of the MIRFLICKR collection with 25'000 objects.