Exaggerating Temporal Differences Enhances Recognition of Individuals from Point Light Displays

Hill, Harold; Pollick, Frank E.

doi:10.1111/1467-9280.00245

Cited by 124 publications

(88 citation statements)

References 24 publications

(24 reference statements)

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“…The importance of spatial configuration in the perception of biological motion has been widely demonstrated (25,(27)(28)(29)(30), whereas only a few have suggested that the temporal properties might also have an impact on the processing of biological motion information (38)(39)(40)(41)(42)(43). For ex- ample, it was found that varying temporal parameters (e.g., display durations and interframe intervals) of point-light walkers modulated participants' performance on a direction discrimination task (39,40).…”

Section: Discussionmentioning

confidence: 99%

“…For ex- ample, it was found that varying temporal parameters (e.g., display durations and interframe intervals) of point-light walkers modulated participants' performance on a direction discrimination task (39,40). Changing temporal properties also affected the recognition of individuals from point-light biological motion displays (42). Although these studies have suggested that temporal characteristics seem to influence how biological motion is perceived, the temporal encoding of biological motion signals remains unclear.…”

Section: Discussionmentioning

confidence: 99%

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Life motion signals lengthen perceived temporal duration

Wang

Jiang

2012

Proc. Natl. Acad. Sci. U.S.A.

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Point-light biological motions, conveying various different attributes of biological entities, have particular spatiotemporal properties that enable them to be processed with remarkable efficiency in the human visual system. Here we demonstrate that such signals automatically lengthen their perceived temporal duration independent of global configuration and without observers' subjective awareness of their biological nature. By using a duration discrimination paradigm, we showed that an upright biological motion sequence was perceived significantly longer than an inverted but otherwise identical sequence of the same duration. Furthermore, this temporal dilation effect could be extended to spatially scrambled biological motion signals, whose global configurations were completely disrupted, regardless of whether observers were aware of the nature of the stimuli. However, such an effect completely disappeared when critical biological characteristics were removed. Taken together, our findings suggest a special mechanism of time perception tuned to life motion signals and shed new light on the temporal encoding of biological motion.point-light walker | temporal expansion | psychometric function O ur senses not only enable our brain to perceive images and sounds, but they also inform us about the passage of time. Time perception over fine scales is fundamental to a range of everyday human activities (for example, to estimate how fast you need to run to catch a ball), and we seem to be able to accurately estimate time as if there exists a specific mechanism that can measure time (e.g., an internal clock; refs. 1, 2). Although it seems quite natural, perceiving time is an extremely complex phenomenon that involves a number of unresolved issues in psychology, and we are far from completely understanding its underlying mechanisms. It has been shown that there is not a specific sensory organ designed to tell time and our representations of subjective temporal duration vary in response to variations of external sensory inputs (reviewed in ref.3).Stimulus motion is thought of as a crucial property that can modulate and alter our perception of time. Several studies have shown that a moving stimulus is perceived to last longer in duration than a slower or stationary stimulus of the same physical duration, a phenomenon referred to as subjective time dilation (4-9). Some researchers proposed that this subjective time dilation effect might reflect a result of long-term evolutionary adaptation (6, 10). By lengthening the subjective duration of those moving and important stimuli and thus enhancing their temporal resolution, observers may be able to process such signals in greater depth per unit of objective time (11), which potentially provides an ecological advantage allowing living organisms to anticipate events or actions and to better adapt themselves to the environment (6). Although the underlying mechanism of the time distortion induced by motion has often been speculated from a point of evolutionary view, all these studies us...

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Life motion signals lengthen perceived temporal duration

Wang

Jiang

2012

Proc. Natl. Acad. Sci. U.S.A.

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“…Purely temporal information from single-point trajectories, for instance, can be sufficient to detect the direction of walking (Mather et al, 1992). Also, the enhanced recognition of individuals found when exaggerating temporal differences in arm movement displays of grasping and drinking out of a glass (Hill & Pollick, 2000) is likely to have been based mostly on motion of the wrist.…”

Section: Influence Of Task Stimulus and Experiencementioning

confidence: 99%

Perception of biological motion from limited-lifetime stimuli

Beintema

Georg

Lappe

2006

Perception & Psychophysics

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“…MLDs images, as feature-based motion cues, have been widely used in studies of visual perception [6][7][8]5,9]; human motion tracking and activity recognition in computer vision [10][11][12][13][14][15]; clinical gait analysis and sports science research [16][17][18][19][20]; character animation [21,22]; augmented reality and virtual reality [14]. Motion analysis from reduced MLDs allows us to use quantitative, concise and accurate data to investigate essential recognition features in visual perception, motion modelling, kinematic formulation and motion synthesis.…”

Section: Introductionmentioning

confidence: 99%

Recognition of human periodic movements from unstructured information using a motion-based frequency domain approach

Meng

Holstein

2006

Image and Vision Computing

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Recognition of Human Periodic Movements From UnstructuredInformation Using A Motion-based Frequency Domain Approach Feature-based motion cues play important role in biological visual perception. We present a motion-based frequency-domain scheme for human periodic motion recognition. As a baseline study of feature-based recognition we use unstructured feature-point kinematic data obtained directly from a marker-based optical motion capture (MoCap) system, rather than accommodate bootstrapping from the low-level image processing of feature detection. Motion power spectral analysis is applied to a set of unidentified trajectories of feature points representing whole body kinematics. Feature power vectors are extracted from motion power spectra and mapped to a low dimensionality of feature space as motion templates that offer frequency domain signatures to characterise different periodic motions. Recognition of a new instance of periodic motion against pre-stored motion templates is carried out by seeking best motion power spectral similarity. We test this method through nine examples of human periodic motion using MoCap data. The recognition results demonstrate that feature-based spectral analysis allows classification of periodic motions from low-level, un-structured interpretation without recovering underlying kinematics. Contrasting with common structure-based spatio-temporal approaches, this motion-based frequency-domain method avoids a time-consuming recovery of underlying kinematic structures in visual analysis and largely reduces the parameter domain in the presence of human motion irregularities.

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Exaggerating Temporal Differences Enhances Recognition of Individuals from Point Light Displays

Cited by 124 publications

References 24 publications

Life motion signals lengthen perceived temporal duration

Life motion signals lengthen perceived temporal duration

Perception of biological motion from limited-lifetime stimuli

Recognition of human periodic movements from unstructured information using a motion-based frequency domain approach

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