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Task-based ideal observer analysis and the efficiency of biological motion percep

基于任务的理想观察者分析与生物运动感知效率

基本信息

批准号：
8008776
负责人：
Jason M Gold
金额：
$ 18万
依托单位：
TRUSTEES OF INDIANA UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-01-01 至 2012-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8008776
关键词：
Address Affect Affective Auditory Behavior Biological Boxing Characteristics Color Complex Data Compression Decision Making Detection Devices Discrimination Disease Electronics Eye Face Future Gender Identity Goals Health Human Human body Laboratories Light Lipreading Measures Mediating Methods Metric Modeling Motion Motion Perception Movement Noise Patients Pattern Pattern Recognition Perception Perceptual learning Performance Play Process Property Psychophysiology Published Comment Relative (related person)Research Research Personnel Retina Role Series Side Signal Detection Analysis Signal Transduction Social Interaction Source Spottings Staging Stimulus System Techniques Technology Testing Theoretical model Time To specify Translating Uncertainty User-Computer Interface Visual Visual Agnosias Visual Motion Visual Perception Visual system structure Work animation base computerized data processing data exchange design disability falls flexibility information processing interest novel novel strategies object recognition research study spatiotemporal visual information visual memory visual process visual processing

项目摘要

DESCRIPTION (provided by applicant): People are able to easily discriminate the movement of humans from other kinds of movement. This ability is sometimes referred to as `biological motion perception', and it has been the focus of a great deal of scientific interest due to the important role it plays in human behavior and social interactions. Although a great deal of research has been carried out to explore various aspects of how we are able to detect and recognize human movement, there has been little or no research that has tried to quantify how much information is carried by the motion of the human body nor how much of this information a human observer is able to use when trying to detect, discrimination or identify human motion. Ideal observer analysis is a technique that allows one to quantitatively answer these questions. Our preliminary results have shown that, contrary to current dogma, human observers make very poor use of information carried by the stimuli and tasks typically used in biological motion experiments. The first set of experiments described in this proposal are designed to build on these results by using a signal-detection based model of visual information processing and a series of system identification techniques to specify the mechanisms that mediate the perception of biological motion. The finding that information use in biological motion perception tasks is so poor has led us to a second, related line of research. The poor use of information we have observed in biological motion perception tasks is actually not uncommon for tasks that involve the perception of complex objects, such as faces and geometric forms. This has led use to ask the question: why is information processing so poor in these tasks? It is our hypothesis that the cause of inefficient information use in these tasks is due to the highly artificial and constrained conditions typically used in psychophysical experiments. Rather, the human visual system has evolved to be robust under conditions of stimulus variability and uncertainty. In this proposal, we outline a new approach called `task-based ideal observer analysis' (TBIOA) that involves the systematic manipulation of a task in order to maximize the human ability to use information. The goal of this approach is to allow us to determine what tasks and stimuli our perceptual systems have evolved to deal with most efficiently. In this proposal, we describe a series of experiments designed to implement and test TBIOA with both simple and complex pattern discrimination tasks. In addition to the immediate goals of the two lines of research described above, there are also several eventual applications of this work. First, this research can be used to inform the design of applications that rely on efficient encoding of information, such as visual data transmission and compression as well as video surveillance technology. Second, this research could potentially be used to help understand how patients with disabilities related to visual perception (e.g., visual agnosias) differ from normal observers and inform how one might design human-machine interfaces to overcome such disabilities. PUBLIC HEALTH RELEVANCE The first goal of the research described in this proposal is to understand how well people use the information that is available to them when they perceive the bodily motions of their fellow humans. The second goal is to develop and test a new modeling approach called "task-based ideal observer analysis", which seeks to determine what tasks and stimuli the human visual system deals with most efficiently. This research has potentially important implications for applications related to data transmission and compression, video surveillance technology and for our eventual understanding and treatment of disorders related to the perception of visual motion (for example, visual agnosias in which people are unable to recognize particular classes of visual motion).

描述（由申请人提供）：人们能够很容易地区分人类的运动和其他类型的运动。这种能力有时被称为“生物运动感知”，由于它在人类行为和社会互动中起着重要作用，它一直是科学界关注的焦点。尽管已经进行了大量的研究来探索我们如何能够检测和识别人体运动的各个方面，但很少或根本没有研究试图量化人体运动携带了多少信息，也没有研究试图量化人类观察者在试图检测、辨别或识别人体运动时能够使用多少这些信息。理想观察者分析是一种可以定量回答这些问题的技术。我们的初步结果表明，与目前的教条相反，人类观察者对生物运动实验中通常使用的刺激和任务所携带的信息的利用非常差。本提案中描述的第一组实验旨在通过使用基于信号检测的视觉信息处理模型和一系列系统识别技术来确定介导生物运动感知的机制，从而建立这些结果。生物运动感知任务中的信息使用如此之少，这一发现将我们引向了第二个相关的研究方向。我们在生物运动感知任务中观察到的对信息的不良利用，实际上在涉及复杂物体感知的任务中并不罕见，比如面部和几何形状。这引发了人们的疑问：为什么这些任务中的信息处理如此糟糕？我们的假设是，这些任务中信息使用效率低下的原因是由于心理物理实验中通常使用的高度人为和受限的条件。相反，人类的视觉系统已经进化到在刺激可变性和不确定性的条件下是稳健的。在本提案中，我们概述了一种名为“基于任务的理想观察者分析”（TBIOA）的新方法，该方法涉及系统地操纵任务，以最大限度地提高人类使用信息的能力。这种方法的目标是让我们确定我们的感知系统已经进化到最有效地处理哪些任务和刺激。在这一提议中，我们描述了一系列旨在通过简单和复杂的模式识别任务来实现和测试TBIOA的实验。除了上述两条研究路线的直接目标之外，这项工作还有几个最终的应用。首先，本研究可用于指导依赖于高效信息编码的应用程序的设计，例如视觉数据传输和压缩以及视频监控技术。其次，这项研究可能被用来帮助理解与视觉感知相关的残疾患者（例如，视觉失认症）与正常观察者的不同之处，并告知人们如何设计人机界面来克服这些残疾。本提案中描述的研究的第一个目标是了解当人们感知到同伴的身体运动时，他们如何利用可获得的信息。第二个目标是开发和测试一种新的建模方法，称为“基于任务的理想观察者分析”，该方法旨在确定人类视觉系统最有效地处理哪些任务和刺激。这项研究对数据传输和压缩、视频监控技术以及我们最终理解和治疗与视觉运动感知相关的疾病（例如，人们无法识别特定类别的视觉运动的视觉失认症）的应用具有潜在的重要意义。

项目成果

期刊论文数量（12）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Discrete-slots models of visual working-memory response times.

DOI：
10.1037/a0034247
发表时间：
2013-10
期刊：
PSYCHOLOGICAL REVIEW
影响因子：
5.4
作者：
Donkin, Christopher;Nosofsky, Robert M.;Gold, Jason M.;Shiffrin, Richard M.
通讯作者：
Shiffrin, Richard M.

Ideal observers and efficiency: commemorating 50 years of Tanner and Birdsall: introduction.

理想的观察者和效率：纪念坦纳和伯索尔成立 50 周年：简介。

DOI：
10.1364/josaa.26.000io1
发表时间：
2009
期刊：
Journal of the Optical Society of America. A, Optics, image science, and vision
影响因子：
0
作者：
Gold,JasonM;Abbey,Craig;Tjan,BoscoS;Kersten,Daniel
通讯作者：
Kersten,Daniel

Efficiencies for parts and wholes in biological-motion perception.