Auer, Peter, Hussain, Zakria, Kaski, Samuel, Klami, Arto, Kujala, Jussi, Laaksonen, Jorma, Leung, Alex P., Pasupa, Kitsuchart and Shawe-Taylor, John (2010) Pinview: Implicit Feedback in Content-Based Image Retrieval In: Workshop on Applications of Pattern Analysis (WAPA 2010), 1-2 September 2010, Cumberland Lodge, UK.
Official URL: https://proceedings.mlr.press/v11/auer10a.html
This paper describes Pinview, a content-based image retrieval system that exploits implicit relevance feedback during a search session. Pinview contains several novel methods that infer the intent of the user. From relevance feedback, such as eye movements or clicks, and visual features of images Pinview learns a similarity metric between images which depends on the current interests of the user. It then retrieves images with a specialized reinforcement learning algorithm that balances the tradeoff between exploring new images and exploiting the already inferred interests of the user. In practise, we have integrated Pinview to the content-based image retrieval system PicSOM, in order to apply it to real-world image databases. Preliminary experiments show that eye movements provide a rich input modality from which it is possible to learn the interests of the user.
Item Type:
Conference or Workshop Item (Paper)
Subjects:
Subjects > Computer Science > Artificial Intelligence
Subjects > Computer Science > Computer Vision and Pattern Recognition
Subjects > Computer Science > Machine Learning
Subjects > Computer Science > Information Retrieval
Subjects > Computer Science > Human-Computer Interaction
Deposited by:
Kitsuchart Pasupa
Date Deposited:
2021-10-22 16:15:53
Last Modified:
2021-10-22 16:22:43