Joint People, Event, and Location Recognition in Personal Photo Collections Using Cross-Domain Context

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• 作者：Dahua Lin ; Ashish Kapoor ; Gang Hua ; Simon Baker
• 刊名：Lecture Notes in Computer Science
• 出版年：2010
• 出版时间：2010
• 年：2010
• 卷：6311
• 期：1
• 页码：243-256
• 全文大小：887.8 KB

文摘

We present a framework for vision-assisted tagging of personal photo collections using context. Whereas previous efforts mainly focus on tagging people, we develop a unified approach to jointly tag across multiple domains (specifically people, events, and locations). The heart of our approach is a generic probabilistic model of context that couples the domains through a set of cross-domain relations. Each relation models how likely the instances in two domains are to co-occur. Based on this model, we derive an algorithm that simultaneously estimates the cross-domain relations and infers the unknown tags in a semi-supervised manner. We conducted experiments on two well-known datasets and obtained significant performance improvements in both people and location recognition. We also demonstrated the ability to infer event labels with missing timestamps (i.e. with no event features).