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WORKSHOP: Doctoral Consortium at the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018)

WORKSHOP: Doctoral Consortium at the IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018)
研讨会:博士联盟在 IEEE 自动人脸和手势识别国际会议 (FG 2018)
批准号:
1829167
负责人:
Yan Tong
金额:
$1.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-04-01 至 2019-03-31

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中文摘要
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英文摘要
This is funding to support a Doctoral Consortium (workshop) of approximately 6 graduate students from U.S. educational institutions, along with unpaid senior members of the research community as mentors, to be held in conjunction with the thirteenth IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018), which will take place May 15-19, 2018, in Xi'an, China. The IEEE FG conference is the premier international forum for research in image- and video-based face, gesture, and body movement recognition. Their broad scope includes new algorithms for computer vision, pattern recognition, and computer graphics, as well as machine learning techniques relevant to face, gesture and body motion for a variety of applications. The conferences present research that advances the state of the art in these and related areas, leading to new capabilities in interactive systems, biometrics, surveillance, healthcare, and entertainment, and they play an important role in shaping related scientific, academic, and educational programs. More information is available online at http://www.fg2018.org/. The Doctoral Consortium will provide an opportunity for Ph.D. students whose dissertations are on topics related to automatic face and gesture recognition to present their proposed research, and receive constructive feedback from an invited committee of faculty and industry researchers, as well as from other students working in these areas. The event will give students valuable exposure to outside perspectives of their work, and provide a comfortable forum in which to discuss and fine-tune their career objectives with members of the international research community, and identify areas that need further development. The workshop will also enable these young researchers to develop a network of contacts at a critical stage of their careers, and will foster a supportive community of scholars and spirit of collaborative research. The organizers will make a particular effort to recruit and include students from underrepresented groups (women and underrepresented minorities) and students from smaller schools or schools with less established computer vision research. They will also try to recruit a demographically diverse (in terms of region, type of employment and stage in career) group of mentors to advise these students.The Doctoral Consortium will be a half-day event during the conference. This year, there will be four distinct aspects to the event. First, each participant will be paired up with an invited faculty or industrial researcher who works in the related area and will act as their mentor both in the Doctoral Consortium and throughout the FG conference. Second, there will be a career panel during a working lunch where participants will have an opportunity to discuss their research and career objectives with other participants and mentors in an informal setting. Third, there will be a dedicated oral session for the students to present their research to the invited committee. Fourth, there will be a poster session for the students to present their work to all conference attendees. These four activities, taken together, will afford an excellent and structured way for students to communicate with other students as well as with established researchers of their related research community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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WORKSHOP: Doctoral Consortium at the IEEE FG 2017 Conference
FG 2013 Doctoral Consortium Proposal for Travel Support for Graduate Students
CAREER: Multimodal and Multialgorithm Facial Activity Understanding by Audiovisual Information Fusion
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