scholarly journals Bird expertise does not increase motion sensitivity to bird flight motion

2021 ◽  
Author(s):  
Simen Hagen ◽  
Quoc Vuong ◽  
Michael D. Chin ◽  
Lisa S. Scott ◽  
Tim Curran ◽  
...  
Keyword(s):  
Moving Objects ◽  
Detection Threshold ◽  
Human Motion ◽  
Inversion Effect ◽  
Local Motion ◽  
Bird Flight ◽  
Motion Sensitivity ◽  
Object Domain ◽  
Terrestrial Movement ◽  
Point Light

While motion information is important for the early stages of vision, it also contributes to later stages of object recognition. For example, human observers can detect the presence of a human, judge its actions, judge its gender and identity simply based on motion cues conveyed in a point-light display. Here we examined whether object expertise enhances the observer’s sensitivity to its characteristic movement. Bird experts and novices were shown point-light displays of upright and inverted birds in flight, or upright and inverted human walkers, and asked to discriminate them from spatially scrambled point-light displays of the same stimuli. While the spatially scrambled stimuli retained the local motion of each dot of the moving objects, it disrupted the global percept of the object in motion. To estimate a detection threshold in each object domain, we systematically varied the number of noise dots in which the stimuli was embedded using an adaptive stair-case approach. Contrary to our predictions, the experts did not show disproportionately higher sensitivity to bird motion, and both groups showed no inversion cost. However, consistent with previous work showing a robust inversion effect for human motion, both groups were more sensitive to upright human walkers than their inverted counterparts. Thus, the result suggests that real-world experience in the bird domain has little-to-no influence on the sensitivity to bird motion, and that birds do not show the typical inversion effect seen with humans and other terrestrial movement.

scholarly journals Flow parsing and biological motion

2021 ◽  
Author(s):  
Katja M. Mayer ◽  
Hugh Riddell ◽  
Markus Lappe
Keyword(s):  
Prior Knowledge ◽  
Relative Motion ◽  
Biological Motion ◽  
Moving Objects ◽  
Human Motion ◽  
Object Motion ◽  
Biological Features ◽  
Typical Object ◽  
Point Light ◽  
Self Motion

AbstractFlow parsing is a way to estimate the direction of scene-relative motion of independently moving objects during self-motion of the observer. So far, this has been tested for simple geometric shapes such as dots or bars. Whether further cues such as prior knowledge about typical directions of an object’s movement, e.g., typical human motion, are considered in the estimations is currently unclear. Here, we adjudicated between the theory that the direction of scene-relative motion of humans is estimated exclusively by flow parsing, just like for simple geometric objects, and the theory that prior knowledge about biological motion affects estimation of perceived direction of scene-relative motion of humans. We placed a human point-light walker in optic flow fields that simulated forward motion of the observer. We introduced conflicts between biological features of the walker (i.e., facing and articulation) and the direction of scene-relative motion. We investigated whether perceived direction of scene-relative motion was biased towards biological features and compared the results to perceived direction of scene-relative motion of scrambled walkers and dot clouds. We found that for humans the perceived direction of scene-relative motion was biased towards biological features. Additionally, we found larger flow parsing gain for humans compared to the other walker types. This indicates that flow parsing is not the only visual mechanism relevant for estimating the direction of scene-relative motion of independently moving objects during self-motion: observers also rely on prior knowledge about typical object motion, such as typical facing and articulation of humans.

scholarly journals Local Dot Motion, Not Global Configuration, Determines Dogs’ Preference for Point-Light Displays

Animals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 661 ◽  
Author(s):  
Carla J. Eatherington ◽  
Lieta Marinelli ◽  
Miina Lõoke ◽  
Luca Battaglini ◽  
Paolo Mongillo
Keyword(s):  
Human Motion ◽  
Visual Preference ◽  
Dog Cognition ◽  
Global Configuration ◽  
Different Types ◽  
Motion Features ◽  
Dot Motion ◽  
Point Light ◽  
Perception Of Biological Motion ◽  
Systematic Manipulation

Visual perception remains an understudied area of dog cognition, particularly the perception of biological motion where the small amount of previous research has created an unclear impression regarding dogs’ visual preference towards different types of point-light displays. To date, no thorough investigation has been conducted regarding which aspects of the motion contained in point-light displays attract dogs. To test this, pet dogs (N = 48) were presented with pairs of point-light displays with systematic manipulation of motion features (i.e., upright or inverted orientation, coherent or scrambled configuration, human or dog species). Results revealed a significant effect of inversion, with dogs directing significantly longer looking time towards upright than inverted dog point-light displays; no effect was found for scrambling or the scrambling-inversion interaction. No looking time bias was found when dogs were presented with human point-light displays, regardless of their orientation or configuration. The results of the current study imply that dogs’ visual preference is driven by the motion of individual dots in accordance with gravity, rather than the point-light display’s global arrangement, regardless their long exposure to human motion.

Advances in Tracking and Recognition of Human Motion

2011 ◽  
pp. 65-71
Author(s):  
Niki Aifanti ◽  
Angel D. Sappa ◽  
Nikos Grammalidis ◽  
Sotiris Grammalidis Malassiotis
Keyword(s):  
Moving Objects ◽  
Research Area ◽  
Initial Position ◽  
Human Motion ◽  
Target Person ◽  
Motion Constraints ◽  
Simplifying Assumptions ◽  
Ill Posed ◽  
Important Research Area ◽  
Tracking And Recognition

Tracking and recognition of human motion has become an important research area in computer vision. In real world conditions it constitutes a complicated problem, considering cluttered backgrounds, gross illumination variations, occlusions, self-occlusions, different clothing and multiple moving objects. These ill-posed problems are usually tackled by making simplifying assumptions regarding the scene or by imposing constraints on the motion. Constraints such as that the contrast between the moving people and the background should be high and that everything in the scene should be static except for the target person are quite often introduced in order to achieve accurate segmentation. Moreover, the motion of the target person is often confined to simple movements with limited occlusions. In addition, assumptions such as known initial position and posture of the person are usually imposed in tracking processes.

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

2020 ◽  
Vol 3 (1) ◽  
pp. 10402-1-10402-11
Author(s):  
Viswadeep Sarangi ◽  
Adar Pelah ◽  
William Edward Hahn ◽  
Elan Barenholtz
Keyword(s):  
Biological Motion ◽  
Human Perception ◽  
Movement Analysis ◽  
Inversion Effect ◽  
Human Gait ◽  
Computational Performance ◽  
Potential Applications ◽  
Perceptual Characteristics ◽  
Point Light ◽  
Perception Of Biological Motion

Abstract 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.

scholarly journals Time perception in human movement: Effects of speed and agency on duration estimation

2020 ◽  
pp. 174702182097951
Author(s):  
Emma Allingham ◽  
David Hammerschmidt ◽  
Clemens Wöllner
Keyword(s):  
Time Perception ◽  
Visual Stimuli ◽  
Time Estimation ◽  
Human Movement ◽  
Human Motion ◽  
Movement Speed ◽  
Acting Out ◽  
Optical Motion ◽  
Point Light ◽  
Duration Estimation

While the effects of synthesised visual stimuli on time perception processes are well documented, very little research on time estimation in human movement stimuli exists. This study investigated the effects of movement speed and agency on duration estimation of human motion. Participants were recorded using optical motion capture while they performed dance-like movements at three different speeds. They later returned for a perceptual experiment in which they watched point-light displays of themselves and one other participant. Participants were asked to identify themselves, to estimate the duration of the recordings, and to rate expressivity and quality of the movements. Results indicate that speed of movement affected duration estimations such that faster speeds were rated longer, in accordance with previous findings in non-biological motion. The biasing effects of speed were stronger for watching others’ movements than for watching one’s own point-light movements. Duration estimations were longer after acting out the movement compared with watching it, and speed differentially affected ratings of expressivity and quality. Findings suggest that aspects of temporal processing of visual stimuli may be modulated by inner motor representations of previously performed movements, and by physically carrying out an action compared with just watching it. Results also support the inner clock and change theories of time perception for the processing of human motion stimuli, which can inform the temporal mechanisms of the hypothesised separate processor for human movement information.

Assessing Lumbar Stabilization from Point-Light and Normal Video Displays of Manual Lifting

1997 ◽  
Vol 85 (3) ◽  
pp. 931-937 ◽  
Author(s):  
Geraldine L. Pellecchia ◽  
Gladys E. Garrett
Keyword(s):  
Visual Perception ◽  
Physical Therapists ◽  
Physical Therapist ◽  
Visual Observation ◽  
Human Motion ◽  
Motor Tasks ◽  
Manual Lifting ◽  
Lumbar Stabilization ◽  
Point Light ◽  
Lifting Task

Routinely, physical therapists use visual observation to assess qualitatively a patient's performance. The literature, however, indicates that assessments of gait and lumbar stabilization from visual observation are at best only moderately reliable. Point-light video displays have been used to study the visual perception of human motion. The present purpose was to examine the reliability of assessments made by a physical therapist when viewing point light and normal video displays of subjects performing a lifting task. Three physical therapists assessed lumbar stabilization by viewing normal and point-light displays of 25 subjects who lifted an 8-lb. milkcrate from floor to waist height. Greater agreement of the therapists' ratings of lumbar stabilization was achieved on assessments made from point-light displays than on those made from normal displays. This finding suggests that the use of point-light displays may improve the reliability of qualitative assessments of performance on motor tasks.

scholarly journals Priming reveals attentional modulation of human motion sensitivity

1998 ◽  
Vol 38 (19) ◽  
pp. 2863-2867 ◽  
Author(s):  
Jane E Raymond ◽  
Helen L O’Donnell ◽  
Steven P Tipper
Keyword(s):  
Human Motion ◽  
Attentional Modulation ◽  
Motion Sensitivity

scholarly journals Center-surround interactions underlie bipolar cell motion sensing in the mouse retina

2021 ◽  
Author(s):  
Sarah Strauss ◽  
Maria M Korympidou ◽  
Yanli Ran ◽  
Katrin Franke ◽  
Timm Schubert ◽  
...  
Keyword(s):  
Bipolar Cell ◽  
Ganglion Cells ◽  
Receptive Fields ◽  
Amacrine Cells ◽  
Bipolar Cells ◽  
Mouse Retina ◽  
Motion Processing ◽  
Local Motion ◽  
Motion Sensing ◽  
Motion Sensitivity

Motion is a critical aspect of vision. We studied the representation of motion in mouse retinal bipolar cells and found, surprisingly, that some bipolar cells possess motion-sensing capabilities that rely on their center-surround receptive fields. Using a glutamate sensor, we directly observed motion-sensitive bipolar cell synaptic output, which was strongest for local motion and dependent on the motion's origin. We characterized bipolar cell receptive fields and found that there are motion and non-motion sensitive bipolar cell types, the majority being motion sensitive. Next, we used these bipolar cell receptive fields along with connectomics to design biophysical models of downstream cells. The models and experiments demonstrated that bipolar cells pass motion-sensitive excitation to starburst amacrine cells through direction-specific signals mediated by bipolar cells' center-surround receptive field structure. As bipolar cells provide excitation to most amacrine and ganglion cells, their motion sensitivity may contribute to motion processing throughout the visual system.

Human Motion Tracking and Recognition

2005 ◽  
pp. 1355-1360
Author(s):  
Niki Aifanti ◽  
Angel D. Sappa ◽  
Nikos Grammalidis ◽  
Sotiris Malassiotis
Keyword(s):  
Motion Tracking ◽  
Moving Objects ◽  
Research Area ◽  
Initial Position ◽  
Human Motion ◽  
Target Person ◽  
Motion Constraints ◽  
Simplifying Assumptions ◽  
Ill Posed ◽  
Tracking And Recognition

Tracking and recognition of human motion has become an important research area in computer vision. In real-world conditions it constitutes a complicated problem, considering cluttered backgrounds, gross illumination variations, occlusions, self-occlusions, different clothing, and multiple moving objects. These ill-posed problems are usually tackled by simplifying assumptions regarding the scene or by imposing constraints on the motion. Constraints such as that the contrast between the moving people and the background should be high, and that everything in the scene should be static except for the target person, are quite often introduced in order to achieve accurate segmentation. Moreover, the motion of the target person is often confined to simple movements with limited occlusions. In addition, assumptions such as known initial position and posture of the person are usually imposed in tracking processes.

Comparative Study of Statistical background Modeling and Subtraction

2017 ◽  
Vol 8 (2) ◽  
pp. 287
Author(s):  
Mourad Moussa ◽  
Maha Hmila ◽  
Ali Douik
Keyword(s):  
Object Detection ◽  
Background Subtraction ◽  
Moving Objects ◽  
Computational Cost ◽  
Gaussian Mixture ◽  
Traffic Monitoring ◽  
Human Motion ◽  
Moving Object Detection ◽  
Moving Object ◽  
Dynamic Scenes

Background subtraction methods are widely exploited for moving object detection in videos in many computer vision applications, such as traffic monitoring, human motion capture and video surveillance. The two most distinguishing and challenging aspects of such approaches in this application field are how to build correctly and efficiently the background model and how to prevent the false detection between; (1) moving background pixels and moving objects, (2) shadows pixel and moving objects. In this paper we present a new method for image segmentation using background subtraction. We propose an effective scheme for modelling and updating a background adaptively in dynamic scenes focus on statistical learning. We also introduce a method to detect sudden illumination changes and segment moving objects during these changes. Unlike the traditional color levels provided by RGB sensor aren’t the best choice, for this reason we propose a recursive algorithm that contributes to select very significant color space. Experimental results show significant improvements in moving object detection in dynamic scenes such as waving tree leaves and sudden illumination change, and it has a much lower computational cost compared to Gaussian mixture model.

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