2005-12-31

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Critical features for the recognition of biological motionCasile & Giese (2005)

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Introduction

Point-light stimuli experimentsPerception of complex biological movements (Johansson, 1973)Not impaired

By adding noise (Cutting et al. 1988)By changing the contrast polarity of the dotsAhlström et al.1997)If only a subset of dots is visibleIf the dots are displaced on the skeleton in every frame

Stimulus Perception

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Introduction

Different Hypotheses

Hypothesis 1: Computational mechanisms reconstruct the missing information from impoverished stimuli by fitting a skeleton model to the stimuli (dots)

most of the existing algorithms are computationally expensive and have no obvious neural implementation

Hypothesis 2: Generalization from normal to point-light stimuli is based on specific features that are shared by both stimulus classes.

The nature of such features is largely unknownIt has been discussed whether they are based on form or motion information Motion Form

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Method

Two movies

Opt

ic F

low

S

timul

us

Stickman walking Moving dots

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Analysis and Results

Two movies

Opt

ic F

low

S

timul

us

Stickman walking Moving dots

PCA

The dominant motion features are very similar for both stimuli, but the The dominant motion features are very similar for both stimuli, but the dominant form features are different. dominant form features are different.

r=0.09

r=0.93

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Psychophysical experiments

CFS Stimulus

Direction

Motion Information

Random Dots

Object 1

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Experiment 1

1AAsymmetric CFS StimulusWritten report about their perceptual impression

13/17: “Human walking”4/17: “jumping dots” or “nothing”

1BSymmetric CFS Stimulus2/9: “Human Walking”4/9: “Human performing actions”3/9 “Nothing” or “The Number 8”

1CRandom dots2/10: “Human Performing actions”8/10: “Nothing”

Arrangement

direction

Motion Information

Random Dots

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Experiment 1

ResultsOpponent motion seems to be critical for generating the impression of a walking human. The presence of moving dots within the same four regions is not sufficient.

Skeleton model hypothesis seems to be wrongCoarse position information is not sufficient to fit this modelThe random dots' positions do not comply with the kinematics of a moving human body

Alternative hypothesis: We use fuzzy templates for the human body shape that fit the CFS in a sub-optimal way

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Experiment 2

MethodIf reconstruction of the human body shape from point positions is critical for the recognition of point-light walkers, then a stimulus that complies with kinematics should be easier recognized than the CFS stimulus

SPS does not affect body shape and matches exactly the human body kinematics1,2,4 dots 1 frame

. .... ... . ... .... .. . ... ..

tFrame 1 Frame 2 Frame 3

VSVS

SPS CFS (Sequential Position Stimulus) (Critical Features Stimulus)

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Experiment 2

Results

No differences between the two stimuliNo precise information about the body shape is neededBoth stimuli might be processed by a common mechanismAsymmetry of the stimulus seems to be an important factor

. .... ... . VSVSSPS CFS

7 SubjectsTask: Recognition of direction of walking

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Neural Model

I. Local Motion Detectors (LMD): small receptive fields, direction preferenceII. Opponent motion detectors: Respond if LMD -within two adjacent subfields- with oposite

direction preference are activeIII. Detectors for complex global optic flow patterns: Larger receptive fields than the whole

point-light stimulus, selectivity established by training, each frame has an optic flow pattern that is encoded by a radial basis function

IV. Motion Pattern Neurons: Sum and temporally smooth the activities of optic flow pattern detectors that belong to the same human action

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Neural Model

Results

Recognition performances for both types of stimuli are very similar.Recognition performance increases with the number of dots in the stimulusRecognition rates for 8 and 4 dots are close to the values obtained in the psychophysical experimentThe recognition rates for 2 dots are lower than human performanceThis model is not able to analyze stimuli with a single dotNo strong increase of performance with the lifetime of dots

High recognition rates can be accomplished solely based on the proposed critical High recognition rates can be accomplished solely based on the proposed critical motion featuremotion featureHigh performance rates for degraded stimuli can be accomplished without complex High performance rates for degraded stimuli can be accomplished without complex computational mechanismscomputational mechanisms

Psychophysical experiment

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Discussion

Normal and point-light stimuli share very similar dominant mid-level optic flow features

The appropriate spatial arrangement of these features induces the percept of a person walking, even though the stimuli do not comply with the kinematics of the human body

The detailed form information provided by the SPS does not seem to improve the recognition of walking direction

A neural model that exploits these critical features achieves substantial recognition rates, even for degraded point-light stimuli

r=0.93

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Discussion

Physiological studies support this computational model (neural detectors for opponent motion)Simple neural circuit. Not complex computational mechanism.

The local motion information can be used for other discrimination tasks (e.g. identification of gait)

http://www.biomotionlab.ca/Demos/BMLwalker.html

Fast

Slow

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Discussion

Physiological studies support this computational model (neural detectors for opponent motion)Simple neural circuit. Not complex computational mechanism.

The local motion information can be used for other discrimination tasks (e.g. identification of gait)

For more difficult tasks, more information might be required.

http://www.biomotionlab.ca/Demos/BMLwalker.html

Female

Male

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Thank you!Thank you!