The interaction between local and global noise for optic-flow patterns

Alan LEE, Chu Ning ANN, Gerrit MAUS

Research output: Other Conference ContributionsPresentationPresentation

Abstract

Both the local and global stages of motion processing are susceptible to noise in the stimulus. Given the hierarchical nature of motion processing, how do the effects of local and global noise interact with each other? If such interaction exists, does it differ across different types of motion patterns? We addressed these questions using a novel psychophysical technique, in which uncertainty at the global and local stages of motion processing was independently manipulated within the same motion stimulus. We used a multiple-aperture motion pattern, which consisted of an array of randomly-oriented, drifting-Gabor elements (Amano et al., 2009). Global noise was manipulated based on motion coherence: Global signal-to-noise ratio (global-SNR) was defined as the ratio between signal and noise element numbers. Signal elements were assigned velocities consistent with a specific global motion direction, while noise elements were assigned velocities based on random global motion directions. Local noise was introduced by superimposing dynamic-noise pixels on each drifting Gabor patch at every motion frame. Local-SNR was defined as the ratio between the contrasts of Gabor patches and noise pixels. Observers performed a 2-choice, global-direction-judgment task on three optic-flow patterns: translational (left vs right), circular (clockwise vs counterclockwise), and radial (inward vs outward). In each block of trials, we fixed local-SNR and measured the 75%-accuracy threshold in terms of global-SNR. For all three optic-flow patterns, we found a "tradeoff" between local and global noise: Global-SNR thresholds decreased log-linearly as local-SNR increased, suggesting an interaction between local and global noise in the motion system. Above a certain local-SNR level, global-SNR thresholds remained constant. This saturation point was lower for circular motion compared to radial and translational optic-flow patterns, suggesting that global integration mechanisms for circular motion are more tolerant to disturbances from local noise.
Original languageEnglish
Publication statusPublished - 15 May 2016
EventVSS 2016 Annual Meeting - TradeWinds Island Resorts, Florida, United States
Duration: 13 May 201618 May 2016
https://www.visionsciences.org/past-meetings/

Conference

ConferenceVSS 2016 Annual Meeting
CountryUnited States
CityFlorida
Period13/05/1618/05/16
Internet address

Fingerprint

Flow patterns
Optics
Signal to noise ratio
Processing
Pixels
Uncertainty

Bibliographical note

On-line version

Cite this

LEE, A., ANN, C. N., & MAUS, G. (2016). The interaction between local and global noise for optic-flow patterns. VSS 2016 Annual Meeting, Florida, United States.
LEE, Alan ; ANN, Chu Ning ; MAUS, Gerrit. / The interaction between local and global noise for optic-flow patterns. VSS 2016 Annual Meeting, Florida, United States.
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LEE, A, ANN, CN & MAUS, G 2016, 'The interaction between local and global noise for optic-flow patterns' VSS 2016 Annual Meeting, Florida, United States, 13/05/16 - 18/05/16, .

The interaction between local and global noise for optic-flow patterns. / LEE, Alan; ANN, Chu Ning; MAUS, Gerrit.

2016. VSS 2016 Annual Meeting, Florida, United States.

Research output: Other Conference ContributionsPresentationPresentation

TY - CONF

T1 - The interaction between local and global noise for optic-flow patterns

AU - LEE, Alan

AU - ANN, Chu Ning

AU - MAUS, Gerrit

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N2 - Both the local and global stages of motion processing are susceptible to noise in the stimulus. Given the hierarchical nature of motion processing, how do the effects of local and global noise interact with each other? If such interaction exists, does it differ across different types of motion patterns? We addressed these questions using a novel psychophysical technique, in which uncertainty at the global and local stages of motion processing was independently manipulated within the same motion stimulus. We used a multiple-aperture motion pattern, which consisted of an array of randomly-oriented, drifting-Gabor elements (Amano et al., 2009). Global noise was manipulated based on motion coherence: Global signal-to-noise ratio (global-SNR) was defined as the ratio between signal and noise element numbers. Signal elements were assigned velocities consistent with a specific global motion direction, while noise elements were assigned velocities based on random global motion directions. Local noise was introduced by superimposing dynamic-noise pixels on each drifting Gabor patch at every motion frame. Local-SNR was defined as the ratio between the contrasts of Gabor patches and noise pixels. Observers performed a 2-choice, global-direction-judgment task on three optic-flow patterns: translational (left vs right), circular (clockwise vs counterclockwise), and radial (inward vs outward). In each block of trials, we fixed local-SNR and measured the 75%-accuracy threshold in terms of global-SNR. For all three optic-flow patterns, we found a "tradeoff" between local and global noise: Global-SNR thresholds decreased log-linearly as local-SNR increased, suggesting an interaction between local and global noise in the motion system. Above a certain local-SNR level, global-SNR thresholds remained constant. This saturation point was lower for circular motion compared to radial and translational optic-flow patterns, suggesting that global integration mechanisms for circular motion are more tolerant to disturbances from local noise.

AB - Both the local and global stages of motion processing are susceptible to noise in the stimulus. Given the hierarchical nature of motion processing, how do the effects of local and global noise interact with each other? If such interaction exists, does it differ across different types of motion patterns? We addressed these questions using a novel psychophysical technique, in which uncertainty at the global and local stages of motion processing was independently manipulated within the same motion stimulus. We used a multiple-aperture motion pattern, which consisted of an array of randomly-oriented, drifting-Gabor elements (Amano et al., 2009). Global noise was manipulated based on motion coherence: Global signal-to-noise ratio (global-SNR) was defined as the ratio between signal and noise element numbers. Signal elements were assigned velocities consistent with a specific global motion direction, while noise elements were assigned velocities based on random global motion directions. Local noise was introduced by superimposing dynamic-noise pixels on each drifting Gabor patch at every motion frame. Local-SNR was defined as the ratio between the contrasts of Gabor patches and noise pixels. Observers performed a 2-choice, global-direction-judgment task on three optic-flow patterns: translational (left vs right), circular (clockwise vs counterclockwise), and radial (inward vs outward). In each block of trials, we fixed local-SNR and measured the 75%-accuracy threshold in terms of global-SNR. For all three optic-flow patterns, we found a "tradeoff" between local and global noise: Global-SNR thresholds decreased log-linearly as local-SNR increased, suggesting an interaction between local and global noise in the motion system. Above a certain local-SNR level, global-SNR thresholds remained constant. This saturation point was lower for circular motion compared to radial and translational optic-flow patterns, suggesting that global integration mechanisms for circular motion are more tolerant to disturbances from local noise.

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M3 - Presentation

ER -

LEE A, ANN CN, MAUS G. The interaction between local and global noise for optic-flow patterns. 2016. VSS 2016 Annual Meeting, Florida, United States.