Word association norms, mutual information, and lexicography
Computational Linguistics
Query expansion using lexical-semantic relations
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
WordNet: a lexical database for English
Communications of the ACM
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
iFind: a web image search engine
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Knowledge-Based Approaches to Query Expansion in Information Retrieval
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
An efficient parts-based near-duplicate and sub-image retrieval system
Proceedings of the 12th annual ACM international conference on Multimedia
A picture is worth a thousand keywords: image-based object search on a mobile platform
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Searching the web with mobile images for location recognition
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Scalable search-based image annotation of personal images
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Dual cross-media relevance model for image annotation
Proceedings of the 15th international conference on Multimedia
A picture is worth a thousand keywords: exploring mobile image-based web search
Proceedings of the 9th international conference on Human computer interaction with mobile devices and services
Improving Web search using image snippets
ACM Transactions on Internet Technology (TOIT)
Photo-based question answering
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Snap and share your photobooks
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Multimodal photo annotation and retrieval on a mobile phone
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
NMF-based multimodal image indexing for querying by visual example
Proceedings of the ACM International Conference on Image and Video Retrieval
Semantic analysis and retrieval in personal and social photo collections
Multimedia Tools and Applications
Flower information retrieval using color feature and location-based system
AICT'11 Proceedings of the 2nd international conference on Applied informatics and computing theory
Multimodal information spaces for content-based image retrieval
FDIA'09 Proceedings of the Third BCS-IRSG conference on Future Directions in Information Access
Image search—from thousands to billions in 20 years
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special Sections on the 20th Anniversary of ACM International Conference on Multimedia, Best Papers of ACM Multimedia 2012
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Nowadays, mobile phones with the digital camera are getting more and more popular. With necessary technologies, they are possible to become a powerful tool to search the Web on the go. Most Web search engines only support text queries. Therefore, users have to convert their information needs into words. However, it is sometimes difficult to describe the needs in text and the text input is inconvenient on small devices. To solve the problem, we propose a system named Photo-to-Search which allows users to input multimodal queries. Particularly, we study queries with captured images and optional text messages in this paper. For example, the user can simply take a photo of the flower and input a few terms like "flower". Textually relevant Web images are retrieved according to the query terms. Afterwards, the snapped picture is compared with these images by the CBIR (Content Based Image Retrieval) method. According to the context of the visually similar images, related key phrases are extracted. Finally, the search results are returned in multiple forms. Our system can also search for very similar images on the Web, such as movie posters or photos of film stars, to find related information. Experimental results on the large scale data showed our system achieved satisfactory efficiency and performance.