The rapid growth of social media in recent years provides a large amount of user-generated visual objects, e.g., images and videos. Advanced semantic understanding approaches on such visual objects are desired to better serve applications such as human-machine interaction, image retrieval, etc. Semantic visual attributes have been proposed and utilized in multiple visual computing tasks to bridge the so-called "semantic gap" between extractable low-level feature representations and high-level semantic understanding of the visual objects.
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- Partial requirement for: Ph.D., Arizona State University, 2016Note typethesis
- Includes bibliographical references (pages 123-129)Note typebibliography
- Field of study: Computer science