报告时间：4月6日星期三
报告地点：紫金港实验室402室
09:30AM – 10:30AM 学术报告，并介绍MSRA研究小组的情况
10:30AM – 11:30AM 参观实验室，和实验室老师以及学生深入交流
MSRA研究小组成员：
华 刚，微软亚洲研究院视觉计算组资深研究员
李志伟，微软亚洲研究院多媒体搜索与挖掘组主管研究员
王太峰，微软亚洲研究院人工智能组主管研究员
童 欣，微软亚洲研究院网络图形组首席研究员
Title: Contextual Person Recognition in Photo Albums
In this talk, we examine the problem of person recognition in photo albums that exploits contextual cues at multiple levels, spanning individual persons, individual photos, and photo groups. At the person level, we leverage clothing and body appearance in addition to facial appearance, and to compensate for instances where the faces are not visible. At the photo level we leverage a learned prior on the joint distribution of identities on the same photo to guide the identity assignments. Going beyond a single photo, we are able to infer natural groupings of photos with shared context in an unsupervised manner. We propose a model to effectively use these complementary multi-level contextual cues to improve overall person recognition accuracy in photo albums. Our results outperform competing methods by a significant margin, while being computationally efficient and practical in a real world application.
Short Bio:
Gang Hua is a Senior Research Manager in the Visual Computing Group at Microsoft Research Asia. His research in computer vision studies the interconnections and synergies among the visual data, the semantic and situated context, and the users in the expanded physical world, which can be categorized into three themes: human centered visual computing, big visual data analytics, and vision based cyber-physical systems. He is the author of more than 100 peer reviewed publications in prestigious international journals and conferences. His research was funded by NSF, NIH, ARO, ONR, Adobe Research, Google Research, Microsoft Research, and NEC Labs. He is the recipient of the 2015 IAPR Young Biometrics Investigator Award. To date, he holds 14 U.S. patents and has more than 10 U.S. patents pending. He is a Senior Member of the IEEE and a life member of the ACM.
