CAREER: A Computational Investigation into Biological Motion Perception
职业:生物运动感知的计算研究
基本信息
- 批准号:0843880
- 负责人:
- 金额:$ 55.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-08-01 至 2014-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
CAREER: A Computational Investigation into Biological Motion PerceptionHongjing Lu, Principal InvestigatorThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).In everyday activities ranging from running in a proper trajectory to avoid hitting other pedestrians, recognizing a friend based upon his walking style from a far distance, to practicing boxing with a partner in the gym, action perception plays a critical role in interpreting the intentions of other people and interacting with the world. Despite the importance of action perception, there are major gaps in our understanding of three basic computational issues: (1) how efficiently human observers can process visual information to make action identifications in different contexts; (2) how humans learn and represent action categories, such as walking, boxing, and dancing; and (3) how humans acquire the ability to understand social interactions by bridging perception and reasoning. With the support of an NSF CAREER award, Dr. Hongjing Lu will integrate computer modeling approaches with behavioral experiments to answer the above three questions. This research will develop greater understanding of how visual information is used to achieve apparently effortless recognition of human actions at different processing levels. The work will significantly extend conventional computational approaches in order to render them applicable to the study of visual processes more complex than those to which they have previously been applied. Understanding the computational basis of action perception is essential to achieving a scientific account of our ability to understand the external world and to conduct social interactions. Furthermore, understanding how the human visual system perceives actions will guide development of artificial vision systems to recognize and interpret complex biological movements. This research will improve a range of applications, including action visualization (e.g., deciding what visual information is important or could be ignored in 3D animation), security surveillance systems (e.g., detection and recognition of suspicious actions in airports or train stations), robotics (e.g., the ability of machines to interact effectively with people), blind assistance system and driver assistance systems (e.g., blind spot detection systems for drivers when backing the car). In addition, the integration of research and education activities in the project will provide students with training opportunities in interdisciplinary research, encompassing psychology, statistics, computer science and mathematics. A new Ph.D. Major in Computational Cognition will be established in the Psychology Department at UCLA. Mathematical training will be promoted at both the graduate and undergraduate levels in Psychology; at the same time, training in experimental research will be introduced to students with mathematical and computer science backgrounds.
职业:生物运动感知的计算研究卢宏静,首席研究员本奖项由2009年美国复苏与再投资法案(公法111-5)资助。在日常活动中,从按照正确的轨迹跑步以避免撞到其他行人,根据远处的走路方式识别朋友,到在健身房与伙伴练习拳击,动作感知在解释他人的意图和与世界互动方面起着至关重要的作用。尽管动作感知很重要,但我们对三个基本计算问题的理解仍存在重大差距:(1)人类观察者如何有效地处理视觉信息以在不同环境下进行动作识别;(2)人类如何学习和表示动作类别,如走路、拳击和跳舞;(3)人类如何通过连接感知和推理来获得理解社会互动的能力。在美国国家科学基金会CAREER奖的支持下,陆宏静博士将结合计算机建模方法和行为实验来回答上述三个问题。这项研究将进一步了解视觉信息是如何在不同的处理水平上毫不费力地实现对人类行为的识别。这项工作将大大扩展传统的计算方法,以便使它们适用于比以前应用的更复杂的视觉过程的研究。理解行动感知的计算基础对于科学地解释我们理解外部世界和进行社会互动的能力至关重要。此外,了解人类视觉系统如何感知动作将指导人工视觉系统的发展,以识别和解释复杂的生物运动。这项研究将改善一系列应用,包括动作可视化(例如,在3D动画中决定哪些视觉信息是重要的或可以忽略的),安全监控系统(例如,机场或火车站可疑行为的检测和识别),机器人技术(例如,机器与人有效互动的能力),盲人辅助系统和驾驶员辅助系统(例如,驾驶员倒车时的盲点检测系统)。此外,研究和教育活动的整合将为学生提供跨学科研究的培训机会,包括心理学、统计学、计算机科学和数学。加州大学洛杉矶分校心理学系将设立一个新的计算认知博士专业。数学训练将在心理学的研究生和本科生阶段得到推广;与此同时,实验研究方面的训练将引入具有数学和计算机科学背景的学生。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Hongjing Lu其他文献
Title Model Selection and Velocity Estimation Using Novel Priors for Motion Patterns Permalink
标题 使用新颖先验进行运动模式的模型选择和速度估计 永久链接
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Shuang Wu;Hongjing Lu;A. Yuille - 通讯作者:
A. Yuille
Evidence from counterfactual tasks supports emergent analogical reasoning in large language models
来自反事实任务的证据支持大型语言模型中的紧急类比推理
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Taylor Webb;K. Holyoak;Hongjing Lu - 通讯作者:
Hongjing Lu
Joints and their relations as critical features in action discrimination: evidence from a classification image method.
关节及其关系作为动作辨别的关键特征:来自分类图像方法的证据。
- DOI:
10.1167/15.1.20 - 发表时间:
2015 - 期刊:
- 影响因子:1.8
- 作者:
Jeroen J. A. van Boxtel;Hongjing Lu - 通讯作者:
Hongjing Lu
Bayesian integration of position and orientation cues in perception of biological and non-biological forms
生物和非生物形式感知中位置和方向线索的贝叶斯整合
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:2.9
- 作者:
Steven M. Thurman;Hongjing Lu - 通讯作者:
Hongjing Lu
Revisiting the importance of common body motion in human action perception
重新审视常见身体运动在人类动作感知中的重要性
- DOI:
10.3758/s13414-015-1031-1 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
Steven M. Thurman;Hongjing Lu - 通讯作者:
Hongjing Lu
Hongjing Lu的其他文献
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{{ truncateString('Hongjing Lu', 18)}}的其他基金
A unified theory for perception of physical and social dynamics
物理和社会动态感知的统一理论
- 批准号:
2142269 - 财政年份:2022
- 资助金额:
$ 55.66万 - 项目类别:
Standard Grant
Discovering Hierarchical Representations for Action Understanding
发现动作理解的层次表示
- 批准号:
1655300 - 财政年份:2017
- 资助金额:
$ 55.66万 - 项目类别:
Standard Grant
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