Does the visual system exploit projective geometry to help solve the motion correspondence problem?

Eagle, Richard A; Hogervorst, Maarten A.; Blake, A.

doi:10.1016/s0042-6989(98)00149-7

Cited by 3 publications

(2 citation statements)

References 34 publications

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“…20 The 3-D internal representation in the HVS and the rigidity hypothesis in correspondence finding, while tracking moving objects, is still a matter of scientific debate. Eagle et al 21 have found a preference toward translation in explaining competing motion transformations in a twoframe sequence with little regard for the projective shape transformations.…”

Section: Mental Transformationmentioning

confidence: 99%

Transformation-aware perceptual image metric

Kellnhofer

Ritschel

Seidel

2016

J. Electron. Imaging

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Predicting human visual perception has several applications such as compression, rendering, editing, and retargeting. Current approaches, however, ignore the fact that the human visual system compensates for geometric transformations, e.g., we see that an image and a rotated copy are identical. Instead, they will report a large, false-positive difference. At the same time, if the transformations become too strong or too spatially incoherent, comparing two images gets increasingly difficult. Between these two extrema, we propose a system to quantify the effect of transformations, not only on the perception of image differences but also on saliency and motion parallax. To this end, we first fit local homographies to a given optical flow field, and then convert this field into a field of elementary transformations, such as translation, rotation, scaling, and perspective. We conduct a perceptual experiment quantifying the increase of difficulty when compensating for elementary transformations. Transformation entropy is proposed as a measure of complexity in a flow field. This representation is then used for applications, such as comparison of nonaligned images, where transformations cause threshold elevation, detection of salient transformations, and a model of perceived motion parallax. Applications of our approach are a perceptual level-of-detail for real-time rendering and viewpoint selection based on perceived motion parallax.

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Section: Mental Transformationmentioning

confidence: 99%

Transformation-aware perceptual image metric

Kellnhofer

Ritschel

Seidel

2016

J. Electron. Imaging

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“…Next, we find the rotation transformation corresponding to the angle e r ¼ arctan 2ðm 21 ; m 11 Þ in radians and remove it by multiplying with an inverse rotation matrix.…”

Section: Transformation Decompositionmentioning

confidence: 99%

A transformation-aware perceptual image metric

Kellnhofer

Ritschel

Seidel

2015

Human Vision and Electronic Imaging XX

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Abstract. Predicting human visual perception has several applications such as compression, rendering, editing, and retargeting. Current approaches, however, ignore the fact that the human visual system compensates for geometric transformations, e.g., we see that an image and a rotated copy are identical. Instead, they will report a large, false-positive difference. At the same time, if the transformations become too strong or too spatially incoherent, comparing two images gets increasingly difficult. Between these two extrema, we propose a system to quantify the effect of transformations, not only on the perception of image differences but also on saliency and motion parallax. To this end, we first fit local homographies to a given optical flow field, and then convert this field into a field of elementary transformations, such as translation, rotation, scaling, and perspective. We conduct a perceptual experiment quantifying the increase of difficulty when compensating for elementary transformations. Transformation entropy is proposed as a measure of complexity in a flow field. This representation is then used for applications, such as comparison of nonaligned images, where transformations cause threshold elevation, detection of salient transformations, and a model of perceived motion parallax. Applications of our approach are a perceptual level-of-detail for real-time rendering and viewpoint selection based on perceived motion parallax. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Perceived global flow direction reveals local vector weighting by luminance

2011

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Global flow occurs when random dots, each selecting their direction of motion randomly each frame from a distribution of directions spanning up to 180°, appear to move as a whole in the mean direction of the components. This percept arises because the visual system integrates the many independent local motion signals over space and time. Through a series of direction discrimination experiments with random-dot cinematograms (RDCs), we show that varying the luminance of dots over a suprathreshold range profoundly affects perceived direction; the brightest dots appear to be weighted more and dimmer dots weighted less when determining perceived global direction. This effect is not observable if all dots in the display have the same luminance but only when the display contains dots with different luminance values. The results are consistent with energy models of motion detectors whose responses are contrast dependent. A Monte Carlo simulation of global direction discrimination employing a 12-mechanism line-element model that weighted the local motion vectors by the normalized squared contrast of the component dots (a proxy for contrast energy) captured well the features of the experimental data.

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Does the visual system exploit projective geometry to help solve the motion correspondence problem?

Cited by 3 publications

References 34 publications

Transformation-aware perceptual image metric

Transformation-aware perceptual image metric

A transformation-aware perceptual image metric

Perceived global flow direction reveals local vector weighting by luminance

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