A psychophysical evaluation of the a contrario detection theory

Blusseau, Samy; Carboni, Alejandra; Maiche, Alejandro; Morel, Jean‐Michel; Gioi, Rafael Grompone von

doi:10.1109/icip.2014.7025217

Cited by 3 publications

(2 citation statements)

References 31 publications

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“…In this sense, a-contrario detection is a parameter-free method. Psychophysical experiments suggest that a-contrario detection matches human perception [24,25].…”

Section: Introductionmentioning

confidence: 90%

An a-contrario approach to quasi-periodic noise removal

Sur

2015

2015 IEEE International Conference on Image Processing (ICIP)

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International audienceImages can be affected by quasi-periodic noise. This undesirable feature manifests itself by spurious repetitive patterns covering the whole image, well localized in the Fourier domain. While notch filtering permits to get rid of this phenomenon , this however requires to first detect the resulting Fourier spikes, and, in particular, to discriminate between noise spikes and spectrum patterns caused by spatially localized textures or repetitive structures. This paper proposes a statistical a-contrario detection of noise spikes in the Fourier domain. A Matlab code is also provided

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“…In this sense, a-contrario detection is a parameter-free method. Psychophysical experiments suggest that a-contrario detection matches human perception [24,25].…”

Section: Introductionmentioning

confidence: 90%

An a-contrario approach to quasi-periodic noise removal

Sur

2015

2015 IEEE International Conference on Image Processing (ICIP)

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“…These analyses are inspired from human ability to develop an understanding of a situation using a limited number of static observations. Human associate these observations with background knowledge in a form of previously seen episodes or past experience [8,4]. This ability allows a human subject to interpret a complex scene from static images and make hypotheses about unseen actions that may have occurred and could explain changes to the scene.…”

Section: Introductionmentioning

confidence: 99%

Recognizing Manipulation Actions from State-Transformations

Aboubakr¹,

Crowley²,

Ronfard³

2019

Preprint

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Manipulation actions transform objects from an initial state into a final state. In this paper, we report on the use of object state transitions as a mean for recognizing manipulation actions. Our method is inspired by the intuition that object states are visually more apparent than actions from a still frame and thus provide information that is complementary to spatio-temporal action recognition. We start by defining a state transition matrix that maps action labels into a pre-state and a post-state. From each keyframe, we learn appearance models of objects and their states. Manipulation actions can then be recognized from the state transition matrix. We report results on the EPIC kitchen action recognition challenge.

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Measuring the visual salience of alignments by their non-accidentalness

et al. 2016

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Quantitative approaches are part of the understanding of contour integration and the Gestalt law of good continuation. The present study introduces a new quantitative approach based on the a contrario theory, which formalizes the non-accidentalness principle for good continuation. This model yields an ideal observer algorithm, able to detect non-accidental alignments in Gabor patterns. More precisely, this parameterless algorithm associates with each candidate percept a measure, the Number of False Alarms (NFA), quantifying its degree of masking. To evaluate the approach, we compared this ideal observer with the human attentive performance on three experiments of straight contours detection in arrays of Gabor patches. The experiments showed a strong correlation between the detectability of the target stimuli and their degree of non-accidentalness, as measured by our model. What is more, the algorithm's detection curves were very similar to the ones of human subjects. This fact seems to validate our proposed measurement method as a convenient way to predict the visibility of alignments. This framework could be generalized to other Gestalts.

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A psychophysical evaluation of the a contrario detection theory

Cited by 3 publications

References 31 publications

An a-contrario approach to quasi-periodic noise removal

An a-contrario approach to quasi-periodic noise removal

Recognizing Manipulation Actions from State-Transformations

Measuring the visual salience of alignments by their non-accidentalness

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