中国生物特征识别大会
张大鹏
香港中文大学（深圳）数据科学学院校长学勤讲座教授，IEEE Life/IAPR/AAIA Fellow
×
张大鹏
中香港中文大学（深圳）数据科学学院校长学勤讲座教授，IEEE Life/IAPR/AAIA Fellow
张大鹏
香港中文大学（深圳）数据科学学院校长学勤讲座教授，IEEE Life/IAPR/AAIA Fellow
简介：
张大鹏，香港中文大学（深圳）数据科学学院校长学勤讲座教授、深圳市人工智能与机器人研究院（AIRS）计算机视觉研究中心主任、港中大（深圳）-联易融计算机视觉与人工智能联合实验室主任。40多年来一直从事模式识别，图像处理以及生物特征识别研究，是掌纹识别、中医四诊量化及人脸美学等研究领域的开创者和领军人。自2005年以来，他一直担任香港理工大学计算学系的讲座教授。其研究成果曾多次获奖，如中韩授予的发明金奖及特殊金奖、日内瓦发明展银奖，以及授予的我国香港特别行政区最高科学技术奖项“裘槎(Chroucher Foundation)优秀科研者”奖等。张教授已出版了20多部相关专著、500余篇国际期刊论文和40多项美国、日本、中国专利。张教授还是IEEE计算机学会杰出演讲人、IEEE Life / IAPR / AAIA Fellow。凭借其在生物特征识别领域的卓越成就，于2020年和2021年分别当选为加拿大皇家科学院和加拿大工程院院士。
报告题目：Advanced Biometrics: 深度探索 泛化应用
报告摘要：In recent times, an increasing, worldwide effort has been devoted to the development of automatic personal identification systems that can be effective in a wide variety of security contexts. As one of the most powerful and reliable means of personal authentication, biometrics has been an area of particular interest. It has led to the extensive study of biometric technologies and the development of numerous algorithms, applications, and systems, which could be defined as Advanced Biometrics. This presentation will systematically explain this new research trend. As case studies, a new biometrics technology (palmprint recognition) and two new biometrics applications (medical biometrics and aesthetical biometrics) are introduced. Some useful achievements could be given to illustrate their effectiveness.
陈熙霖
中国科学院计算技术研究所所长兼党委书记，ACM/CCF/IAPR/IEEE Fellow
×
陈熙霖
中国科学院计算技术研究所所长兼党委书记，ACM/CCF/IAPR/IEEE Fellow
陈熙霖
中国科学院计算技术研究所所长兼党委书记，ACM/CCF/IAPR/IEEE Fellow
简介：
陈熙霖，研究员，现任中国科学院计算技术研究所所长兼党委书记，ACM/CCF/IAPR/IEEE Fellow, 国家杰出青年基金获得者。主要研究领域为计算机视觉、模式识别、多媒体技术以及多模式人机接口。曾主持国家自然科学基金重大、重点项目、973计划课题、863计划项目等的研究。曾任IEEE TIP和IEEE TMM的AE，目前担任Journal of Visual Communication and Image Representation的Senior AE、计算机学报和模式识别与人工智能的副主编。担任过FG2013 / 2018、ChinaMM 2018 / 2019和PRCV 2019 / 2020大会主席，并多次担任CVPR和ICCV等的领域主席，获CCF-CV杰出成就奖。在国内外重要刊物和会议上发表论文300多篇，先后获得国家自然科学二等奖一项，国家科技进步二等奖四项。
报告题目：生物特征识别的隐私与安全
报告摘要：生物特征识别技术的广泛使用给百姓生活和社会治理带来了极大的方便，同时也产生了极大的安全和隐私隐患。近年来世界各国对人工智能技术特别是生物特征识别使用的安全、伦理、隐私等问题制定了一系列的法规。生物特征识别技术安全可靠的使用，一方面有赖于法律法规的健全，同时也和技术本身的进步以及合理使用有着极大的关系。如何防止身份假冒与盗用等安全和隐私问题，在技术上应该采取哪些措施加以防范是生物特征识别领域值得关注的问题。报告将从生物特征识别技术应用的历史变迁探讨其中的问题，同时将报告一些近年来在这方面研究的探索与进展。
Massimo Tistarelli
意大利萨萨里大学终身教授，IAPR Fellow
×
Massimo Tistarelli
意大利萨萨里大学终身教授，IAPR Fellow
Massimo Tistarelli
意大利萨萨里大学终身教授，IAPR Fellow
简介：
Massimo Tistarelli is currently a Tenured Full Professor of Computer Science and the Director of the Computer Vision Laboratory, University of Sassari, Italy. He received the Ph.D. degree in computer science and robotics from the University of Genoa, Italy, in 1991. His main research interests cover biological and artificial vision, pattern recognition, biometrics, visual sensors, robotic navigation, and visuomotor coordination. He is one of the world-recognized leading researchers in biometrics and has directed the Summer School on Biometrics for the past 20 years. He is AE for IVC, IET Biometrics and PR and was AE for TPAMI and PRL. He served as chair of the IEEE Italian Chapter of the Biometrics Council for two terms, the IAPR Technical Committee on Biometrics and the First Vice President of the IAPR (2014-2018). He has served as Vice-President Technical Activities of the IEEE Biometrics Council (2019-2021), chair of the IAPR Fellow Committee (2018-), member of the IEEE Distinguished Lecturers Program. He has also served as member of the IEEE Biometrics Certification Program. He is a fellow of the IAPR, Senior Member of the IEEE.
报告题目：Face Recognition: a Vision Ahead Reflections on 30 years of face recognition research
报告摘要：Face recognition is possibly one of the most successful applications of Computer Vision and AI. Today's information technology allowed to deploy face recognition in several domains, ranging from automated border control to mobile device authentication. Even though the progress in computing power and machine learning allowed to implement very fast and efficient systems, there are still several issues which remain unsolved. On the other hand, the basic "face recognition pipeline", conceived 30 years ago, still remains unaltered. As such, we need to learn from the past and address some research questions which are still unanswered. Among them:
1. If face recognition is a "solved" problem, why are we still doing research on this topic?
2. What are the drawbacks and limitations of current deep learning models? How far can we go by exploiting increasing amounts of face data?
3. Is the human visual system still the best comparative face recognition model? If so, what can we learn from the way humans recognize faces?
4. How can we build "ethical" systems which properly address current privacy concerns?
In this talk we'll address these questions, trying to envisage a path forward with the aim of driving our research curiosity towards the design of tomorrow's intelligent machines.
赵国英
芬兰科学院教授、芬兰奥卢大学终身教授，IEEE/IAPR/ELLIS/AAIA Fellow
×
赵国英
芬兰科学院教授、芬兰奥卢大学终身教授，IEEE/IAPR/ELLIS/AAIA Fellow
赵国英
芬兰科学院教授、芬兰奥卢大学终身教授，IEEE/IAPR/ELLIS/AAIA Fellow
简介：
赵国英，现任芬兰科学院教授、芬兰奥卢大学机器视觉和信号分析中心（终身）教授、芬兰科学与人文院院士、欧洲科学院院士，IEEE / IAPR / ELLIS / AAIA Fellow。其研究方向为计算机视觉、情感计算、机器学习、人工智能等。她发表学术论文320余篇，谷歌学术引用26240余次，研究成果曾被芬兰国家电视台、加拿大Technology Discovery TV和《麻省理工科技评论》等报道。她主持了二十余项芬兰、欧盟和国际合作科研项目，指导的三十多位博士后和博士生已有多位成为教授，一位获得芬兰科学院Fellow职位，两位获得芬兰科学院博士后职位，多位获得极具竞争力的国际和国内奖项。她（曾）是PR、IEEE TCSVT、IEEE TMM、IVC、JEI等多个国际期刊的编委（AE），是芬兰人工智能协会董事会成员，ICMI 2021等国际会议的程序主席和大会主席。她先后被评为Nokia访问教授、欧洲华人十大科技领军人才和2020芬兰华人学生学者年度人物等。
报告题目：远程心跳检测的前世今生
报告摘要：Physiological signals, including e.g., heart rate (HR), heart rate variability (HRV), and respiratory frequency (RF) are important indicators of our health, which are usually measured in clinical examinations. Traditional physiological signal measurement often involves contact sensors, which is inconvenient or cause discomfort in long-term monitoring sessions. This talk focuses on studies exploring remote HR measurement from facial videos, from early developed hand-crafted to later proposed deep learning based methods, together with a new Oulu Bio-Face (OBF) database as a benchmark dataset. Moreover, applications of remote heart rate measure are presented, including e.g., atrial fibrillation (AF) screening and face anti-spoofing, with the video-extracted heart rate related features.
虞晶怡
上海科技大学副教务长、信息科学与技术学院教授、院长，OSA / IEEE Fellow
×
虞晶怡
上海科技大学副教务长、信息科学与技术学院教授、院长，OSA / IEEE Fellow
虞晶怡
上海科技大学副教务长、信息科学与技术学院教授、院长，OSA / IEEE Fellow
简介：
虞晶怡，现任上海科技大学副教务长、信息科学与技术学院教授、院长，OSA / IEEE Fellow，ACM杰出科学家，智能感知与人机协同教育部重点实验室主任。他于2000年获美国加州理工学院（Caltech）双学士学位，2005年获美国麻省理工学院（MIT）博士学位。现任上海科技大学副教务长、信息科学与技术学院教授、院长。虞教授长期从事计算机视觉、计算成像、计算机图形学、生物信息学等领域的研究工作，并先后获得美国国家科学基金杰出青年奖（NSF CAREER Award），美国空军研究院杰出青年奖 (AFOSR YIP Award)，白玉兰纪念奖。在智能光场研究上，他拥有十余项国际PCT专利，已广泛应用于智慧城市、数字人、人机交互等场景。他曾经担任IEEE TPAMI、IEEE TIP等多个顶级期刊编委，并担任国际人工智能顶会CVPR 2021和ICCV 2027的程序主席、ICCV 2025的大会主席。他是达沃斯世界经济论坛（WEF）“全球议程理事会”理事。
报告题目：Beyond Visual Biometric Signals
报告摘要：Most existing biometrics are based on visual signals. In this talk, I discuss the possibility of using signals beyond the ones captured by traditional RGB cameras. This work is inspired by our latest efforts on constructing digital humans more than their appearances, by incorporating anatomical structures. For example, we have previously used XRay and MRI to capture the inner structures (bones, muscles, etc) of faces and hands as well as use IMU units to capture whole body movements. I show many of these signals can potentially serve as new types of biometrics and benefit applications where RGB signals fail (e.g., low light, long range, fast movements, etc).
孙哲南
中国科学院自动化研究所研究员
×
孙哲南
中国科学院自动化研究所研究员
孙哲南
中国科学院自动化研究所研究员
简介：中国科学院自动化研究所研究员、国家万人领军人才，主持10余项国家级科研项目，发表300多篇论文，授权发明专利56项，孵化3家高科技企业，获国家技术发明二等奖、中国图象图形学学会自然科学一等奖、吴文俊人工智能科学技术进步奖、北京市科技进步二等奖。
报告题目：可感、可知、可信的生物特征识别
报告摘要：生物识别发展在人工智能时代有广阔发展前景，不论是生物特征传感器、识别算法还是安全防御机制处于理论创新、技术突破、产业应用的战略机遇期。生物特征识别领域存在三大挑战问题——“感知盲区”、“决策误区”和“安全红区”，必须变革和创新生物特征的传感、认知、安全机制，才有可能取得复杂场景生物识别的根本性突破，“可感”、“可知”、“可信”是新一代生物特征识别的总体目标。