Neural and Neuromimetic Perception: A Comparative Study of Gender Classification from Human Gait

Humans are adept at perceiving biological motion for purposes such as the discrimination of gender. Observers classify the gender of a walker at significantly above chance levels from a point-light distribution of joint trajectories. However, performance drops to chance level or below for vertically inverted stimuli, a phenomenon known as the inversion effect. This lack of robustness may reflect either a generic learning mechanism that has been exposed to insufficient instances of inverted stimuli or the activation of specialized mechanisms that are pre-tuned to upright stimuli. To address this issue, the authors compare the psychophysical performance of humans with the computational performance of neuromimetic machine-learning models in the classification of gender from gait by using the same biological motion stimulus set. Experimental results demonstrate significant similarities, which include those in the predominance of kinematic motion cues over structural cues in classification accuracy. Second, learning is expressed in the presence of the inversion effect in the models as in humans, suggesting that humans may use generic learning systems in the perception of biological motion in this task. Finally, modifications are applied to the model based on human perception, which mitigates the inversion effect and improves performance accuracy. The study proposes a paradigm for the investigation of human gender perception from gait and makes use of perceptual characteristics to develop a robust artificial gait classifier for potential applications such as clinical movement analysis

Gender Perception From Gait: A Comparison Between Biological, Biomimetic and Non-biomimetic Learning Paradigms

This paper explores in parallel the underlying mechanisms in human perception of biological motion and the best approaches for automatic classification of gait. The experiments tested three different learning paradigms, namely, biological, biomimetic, and non-biomimetic models for gender identification from human gait. Psychophysical experiments with twenty-one observers were conducted along with computational experiments without applying any gender specific modifications to the models or the stimuli. Results demonstrate the utilization of a generic memory based learning system in humans for gait perception, thus reducing ambiguity between two opposing learning systems proposed for biological motion perception. Results also support the biomimetic nature of memory based artificial neural networks (ANN) in their ability to emulate biological neural networks, as opposed to non-biomimetic models. In addition, the comparison between biological and computational learning approaches establishes a memory based biomimetic model as the best candidate for a generic artificial gait classifier (83% accuracy, p < 0.001), compared to human observers (66%, p < 0.005) or non-biomimetic models (83%, p < 0.001) while adhering to human-like sensitivity to gender identification, promising potential for application of the model in any given non-gender based gait perception objective with superhuman performance

Matching Voice and Face Identity From Static Images

Previous research has suggested that people are unable to correctly choose which unfamiliar voice and static image of a face belong to the same person. Here, we present evidence that people can perform this task with greater than chance accuracy. In Experiment 1, participants saw photographs of two, same-gender models, while simultaneously listening to a voice recording of one of the models pictured in the photographs and chose which of the two faces they thought belonged to the same model as the recorded voice. We included three conditions: (a) the visual stimuli were frontal headshots (including the neck and shoulders) and the auditory stimuli were recordings of spoken sentences; (b) the visual stimuli only contained cropped faces and the auditory stimuli were full sentences; (c) we used the same pictures as Condition 1 but the auditory stimuli were recordings of a single word. In Experiment 2, participants performed the same task as in Condition 1 of Experiment 1 but with the stimuli presented in sequence. Participants also rated the model&apos;s faces and voices along multiple &quot;physical&quot; dimensions (e.g., weight,) or &quot;personality&quot; dimensions (e.g., extroversion); the degree of agreement between the ratings for each model&apos;s face and voice was compared to performance for that model in the matching task. In all three conditions, we found that participants chose, at better than chance levels, which faces and voices belonged to the same person. Performance in the matching task was not correlated with the degree of agreement on any of the rated dimensions

Language familiarity modulates relative attention to the eyes and mouth of a talker

a b s t r a c t We investigated whether the audiovisual speech cues available in a talker&apos;s mouth elicit greater attention when adults have to process speech in an unfamiliar language vs. a familiar language. Participants performed a speech-encoding task while watching and listening to videos of a talker in a familiar language (English) or an unfamiliar language (Spanish or Icelandic). Attention to the mouth increased in monolingual subjects in response to an unfamiliar language condition but did not in bilingual subjects when the task required speech processing. In the absence of an explicit speech-processing task, subjects attended equally to the eyes and mouth in response to both familiar and unfamiliar languages. Overall, these results demonstrate that language familiarity modulates selective attention to the redundant audiovisual speech cues in a talker&apos;s mouth in adults. When our findings are considered together with similar findings from infants, they suggest that this attentional strategy emerges very early in life

Language Familiarity Modulates Relative Attention to the Eyes and Mouth of a Talker

Data from article of the same name to be published in Cognitio

Visual comparisons within and between object parts: evidence for a single-part superiority effect

AbstractSubjects judged whether two marks placed at different positions along a curved contour were physically the same. When targets were separated by a concave curvature extremum––corresponding to a part-boundary––decision latencies were longer than when they straddled an equally curved convex extremum, demonstrating a “single-part superiority effect”. This difference increased with both stimulus duration and the magnitude of contour curvature. However, it disappeared when the global configuration was not consistent with a part-boundary interpretation, suggesting a critical role of global organization in part decomposition

Multisensory Associative-Pair Learning: Evidence for ‘Unitization ’ as a specialized mechanism

Learning about objects typically involves the association of multisensory attributes. Here, we present three experiments supporting the existence of a specialized form of associative learning that depends on ‘unitization’. When multisensory pairs (e.g. faces and voices) were likely to both belong to a single object, learning was superior than when the pairs were not likely to belong to the same object. Experiment 1 found that learning of face-voice pairs was superior when the members of each pair were the same gender vs. opposite gender. Experiment 2 found a similar result when the paired associates were pictures and vocalizations of the same species vs. different species (dogs and birds). In Experiment 3, gender-incongruent video and audio stimuli were dubbed, producing an artificially unitized stimulus reducing the congruency advantage. Overall, these results suggest that unitizing multisensory attributes into a single object or identity is a specialized form of associative learnin