Biomedical subjects

Frank E Pollick

Publications and source records attributed to Frank E Pollick.

4 recordsLinked to original sources

PubMed2006

A motion capture library for the study of identity, gender, and emotion perception from biological motion.

We present the methods that were used in capturing a library of human movements for use in computer-animated displays of human movement. The library is an attempt to systematically tap into and represent the wide range of personal properties, such as identity, gender, and emotion, that are available in a person's movements. The movements from a total of 30 nonprofessional actors (15 of them female) were captured while they performed walking, knocking, lifting, and throwing actions, as well as their combination in angry, happy, neutral, and sad affective styles. From the raw motion capture data, a library of 4,080 movements was obtained, using techniques based on Character Studio (plug-ins for 3D Studio MAX, AutoDesk, Inc.), MATLAB The MathWorks, Inc.), or a combination of these two. For the knocking, lifting, and throwing actions, 10 repetitions of the simple action unit were obtained for each affect, and for the other actions, two longer movement recordings were obtained for each affect. We discuss the potential use of the library for computational and behavioral analyses of movement variability, of human character animation, and of how gender, emotion, and identity are encoded and decoded from human movement.

Adolescent↗

PubMed2005

Gender recognition from point-light walkers.

Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal observer for gender recognition on the basis of center of moment (J. E. Cutting, D. R. Proffitt, & L. T. Kozlowski, 1978) and, with the use of anthropometric data from various populations, show optimal recognition of approximately 79% correct. Next, they perform a meta-analysis of 21 experiments examining gender recognition, obtaining accuracies of 66% correct for a side view and 71% for other views. Finally, results of the meta-analysis and the ideal observer are combined to obtain estimates of human efficiency at gender recognition of 26% for the side view and 47% for other views.

Adolescent↗

PubMed2003

Recognising facial expression from spatially and temporally modified movements.

We examined how the recognition of facial emotion was influenced by manipulation of both spatial and temporal properties of 3-D point-light displays of facial motion. We started with the measurement of 3-D position of multiple locations on the face during posed expressions of anger, happiness, sadness, and surprise, and then manipulated the spatial and temporal properties of the measurements to obtain new versions of the movements. In two experiments, we examined recognition of these original and modified facial expressions: in experiment 1, we manipulated the spatial properties of the facial movement, and in experiment 2 we manipulated the temporal properties. The results of experiment 1 showed that exaggeration of facial expressions relative to a fixed neutral expression resulted in enhanced ratings of the intensity of that emotion. The results of experiment 2 showed that changing the duration of an expression had a small effect on ratings of emotional intensity, with a trend for expressions with shorter durations to have lower ratings of intensity. The results are discussed within the context of theories of encoding as related to caricature and emotion.

Caricatures as Topic↗

PubMed2002

Estimating the efficiency of recognizing gender and affect from biological motion.

It is often claimed that point-light displays provide sufficient information to easily recognize properties of the actor and action being performed. We examined this claim by obtaining estimates of human efficiency in the categorization of movement. We began by recording a database of three-dimensional human arm movements from 13 males and 13 females that contained multiple repetitions of knocking, waving and lifting movements done both in an angry and a neutral style. Point-light displays of each individual for all of the six different combinations were presented to participants who were asked to judge the gender of the model in Experiment 1 and the affect in Experiment 2. To obtain estimates of efficiency, results of human performance were compared to the output of automatic pattern classifiers based on artificial neural networks designed and trained to perform the same classification task on the same movements. Efficiency was expressed as the squared ratio of human sensitivity (d') to neural network sensitivity (d'). Average results for gender recognition showed a proportion correct of 0.51 and an efficiency of 0.27%. Results for affect recognition showed a proportion correct of 0.71 and an efficiency of 32.5%. These results are discussed in the context of how different cues inform the recognition of movement style.

Affect↗