Evaluating visual query methods for articulated motion video search

2015 
Abstract We develop and evaluate three interfaces for video search of articulated objects, specifically humans performing common actions. The three interfaces, (1) a freehand interface with motion cues (e.g., arrows), (2) an articulated human stick figure with motion cues, and (3) a keyframe interface, were designed to allow users to quickly generate motion-based queries. We performed both quantitative and qualitative analyses of the interfaces through a formal user study by measuring accuracy and speed of user input and asking the users to complete a free-response questionnaire. Our results indicate that the constrained interfaces outperform the freehand sketch-based interface, in terms of both search accuracy and query completion time. Additionally, the users described strong preferences for the search interfaces containing pre-defined models, and the generated queries were rated higher, in terms of semantic matches to the query concept.
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