Data Fusion for Sensory Information Processing Systems

Clark, James J.; Yuille, Alan

doi:10.1007/978-1-4757-2076-1

Cited by 416 publications

(300 citation statements)

References 77 publications

(168 reference statements)

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“…Perceived quantitative depth is conventionally thought to be derived by combining estimates from individual depth cues in some statistically optimal manner (e.g., Buckley & Frisby, 1993;Bülthoff & 6 Mallot, 1988;Clark & Yuille, 1990;Landy, Maloney, Johnston & Young, 1995). The depth cues available from a single eye in static scenes are usually referred to as pictorial or monocular depth cues.…”

Section: Pictures Monocular Vs Binocular Viewing)mentioning

confidence: 99%

Toward a new theory of stereopsis.

Vishwanath¹

2014

Psychological Review

208

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Humans can obtain an unambiguous perception of depth and 3-dimensionality with one eye or when viewing a pictorial image of a 3-dimensional scene. However, the perception of depth when viewing a real scene with both eyes is qualitatively different: there is a vivid impression of tangible solid form and immersive negative space. This perceptual phenomenon, referred to as "stereopsis", has been among the central puzzles of perception since the time of da Vinci. After Wheatstone's invention of the stereoscope in 1838, stereopsis has conventionally been explained as a by-product of binocular vision or visual parallax. However, this explanation is challenged by the observation that the impression of stereopsis can be induced in single pictures under monocular viewing. Here I propose an alternative hypothesis that stereopsis is a qualitative visual experience related to the perception of egocentric spatial scale. Specifically, the primary phenomenal characteristic of stereopsis (the impression of 'real' separation in depth) is proposed to be linked to the precision with which egocentrically scaled depth (absolute depth) is derived. Since conscious awareness of this precision could help guide the planning of motor action, the hypothesis provides a functional account for the important phenomenal characteristic associated with stereopsis: the impression of interactability. By linking stereopsis to a generic perceptual attribute, rather than a specific cue, it provides a potentially more unified account of the variation of stereopsis in real scenes and pictures, and a basis for understanding why we can perceive depth in pictures despite conflicting visual signals. StereopsisVishwanath 3

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Section: Pictures Monocular Vs Binocular Viewing)mentioning

confidence: 99%

Toward a new theory of stereopsis.

Vishwanath¹

2014

Psychological Review

208

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“…This problem is receiving an increasing amount of attention (Biilthoff & Mallot, 1988;Aloimonos & Shulman, 1989;Maloney & Landy, 1989). Clark and Yuille (1990) divide approaches to the problem into weak fision and strong fusion models. Research on single depth cues has fostered an understanding of depth perception as a system of modular processes (Marr, 1982) and weak fusion models emphasize the apparently modular structure of depth vision.…”

Section: Introductionmentioning

confidence: 99%

A perturbation analysis of depth perception from combinations of texture and motion cues

1993

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We examined how depth information from two different cue types (object motion and texture gradient) is integrated into a single estimate in human vision. Two critical assumptions of a recent'model of depth cue combination (termed moa!i@d weak fusion) were tested. The first assumption is that the overall depth estimate is a weighted linear combination of the estimates derived from the individual cues, after initial processing needed to bring them to a common format. The second assumption is that the weight assigned to a cue reflects the apparent reliability of that cue in a particular scene. By this account, the depth combination rule is linear and dynamic, changing in a predictable fashion in response to the particular scene and viewing conditions. A novel procedure was used to measure the weights assigned to the texture and motion cues across experimental conditions. This procedure uses a type of perturbation analysis. The results are consistent with the weighted linear combination rule. In addition, when either cue is corrupted by added noise, the weighted linear combination rule shifts in favor of the uncontaminated cue.

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“…A general definition of image fusion is given as "Image fusion is the combination of two or more different images to form a new image by using a certain algorithm" [17,18,19]. It aims at obtaining information of greater quality; the exact definition of 'greater quality' will depend upon the application [20].…”

Section: Image Fusionmentioning

confidence: 99%

Modulated AIHT Image Contrast Enhancement Algorithm based on Contrast-Limited Adaptive Histogram Equalization

Yu¹,

Lin²,

Yu³

2013

Appl. Math. Inf. Sci.

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Abstract:The Adaptive Inverse Hyperbolic Tangent (AIHT) algorithm is capable of enhancing the global contrast of the original image adaptively, while extruding the details of objects simultaneously, cannot enhance local contrast. Therefore, we proposed a ContrastLimited Adaptive Histogram Equalization (CLAHE) modulation based on AIHT contrast enhancement algorithm from conjugate AIHT and CLAHE image contrast enhance algorithm. The CLAHE has good contrast enhance performance, but excessive contrast enhance will produce the serious chromatic aberration results. We apply the AIHT and CLAHE advantage to present a joint multiple processes algorithm of contrast enhancement to achieve better contrast enhancement effect.

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Data Fusion for Sensory Information Processing Systems

Abstract: 1957-Data fusion for sensory information processing systems / James J. Clark, Alan L. Yuille. p. cm. -Kluwer international series in engineering and computer science ; SECS 105) Includes bibliographical references (p. ) and index. ISBN 978-1-4419-5126-7 ISBN 978-1-4757-2076-1 (eBook)

Cited by 416 publications

References 77 publications

Toward a new theory of stereopsis.

Toward a new theory of stereopsis.

A perturbation analysis of depth perception from combinations of texture and motion cues

Modulated AIHT Image Contrast Enhancement Algorithm based on Contrast-Limited Adaptive Histogram Equalization

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