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MARQS: RETRIEVING SKETCHES USING DOMAIN- AND STYLE-INDEPENDENT FEATURES LEARNED FROM A SINGLE EXAMPLE USING
| Content Provider | CiteSeerX |
|---|---|
| Author | Dual-Classifier, A. Paulson, Brandon |
| Abstract | Mouse and keyboard interfaces handle traditional text-based queries, and standard search engines provide for effective text-based search. However, everyday documents are filled with not only text, but photos, cartoons, diagrams, and sketches. These images can often be easier to recall than the surrounding text. In an effort to make human-computer interaction imitate more forms of human-human interaction, sketching has recently become an important means of interacting with computer systems. We propose extending the traditional mono-modal model of text-based search to include the capabilities of sketch-based search. Our goal is to create a sketch-based search algorithm that can find documents from a single query sketch. We imagine an important use for this technology would be to allow users to search a computerized laboratory notebook for a previously drawn sketch. Because such a sketch will have initially been drawn only a single time, it is important that the search-by-sketch system 1) recognize a wide range of shapes that are not necessarily simple geometric shapes nor drawn identically each time, 2) recognize a query example from only one initial training example, and 3) learn from successful queries to improve accuracy over time. We present here such an algorithm. To test the algorithm, we implemented a proof-of-concept-system: MARQS, a system that uses sketches to query existing media albums. Preliminary results show that the system yielded an average search rank of 1.51, indicating that the correct sketch is presented as either the top or second search result on average. We also discuss the usability of this system. KEYWORDS sketch recognition – sketch-based interfaces – search by sketch – feature-based recognition 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Sketch-based Search Effective Text-based Search Important Use Search-by-sketch System Single Query Sketch Human-computer Interaction Imitate Standard Search Engine Average Search Rank Human-human Interaction Successful Query Computerized Laboratory Notebook Computer System Traditional Mono-modal Model Query Example Sketch Feature-based Recognition Single Time Medium Album Important Mean Everyday Document Simple Geometric Shape Correct Sketch Text-based Search Second Search Result Interface Handle Traditional Text-based Query |
| Content Type | Text |
