Two carriers for motion perception: Color and luminance

Papathomas, Thomas V.; Goréa, Andrei; Julesz, Béla

doi:10.1016/0042-6989(91)90183-6

Cited by 67 publications

(27 citation statements)

References 26 publications

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“…In general, motion perception is weaker at isoluminance than with luminance contrast present, but there is nevertheless good evidence for a chromatic input to at least some types of motion processing (Cavanagh & Favreau, 1985;Cropper & Derrington, 1996;Green, 1989;Morgan & Ingle, 1994;Mullen & Baker, 1985;Palmer, Mobley, & Teller, 1993;Papathomas, Gorea, & Julesz, 1991;Saito, Tanaka, Isono, Yasuda, & Mikami, 1989;Yoshizawa, Mullen, & Baker, 2000). That color might facilitate motion processing by helping segregate target elements from distractors is, however, not necessarily contingent on motion perception being possible at isoluminance.…”

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confidence: 91%

Segregation by color/luminance does not necessarily facilitate motion discrimination in the presence of motion distractors

Kingdom

2001

Perception & Psychophysics

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Under what circumstances is the common motion of a group of elements more easily perceived when the elements differ in color and/or luminance polarity from their surround? Croner and Albright (1997), using a conventional global motion paradigm, first showed that motion coherence thresholds fell when target and distractor elements were made different in color. However, in their paradigm, there was a cue in the static view of the stimulus as to which elements belonged to the target. Arguably, in order to determine whether the visual system automatically groups, or prefilters, the image into different color maps for motion processing, such static form cues should be eliminated. Using various arrangements of the global motion stimulus in which we eliminated all static form cues, we found that global motion thresholds were no better when target and distractors differed in color than when they were identical, except under certain circumstances in which subjects had prior knowledge of the specific target color. We conclude that, in the absence of either static form cues or the possibility of selective attention to the target color, features with similar colors/luminance-polarities are not automatically grouped for global motion analysis.

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confidence: 91%

Segregation by color/luminance does not necessarily facilitate motion discrimination in the presence of motion distractors

Kingdom

2001

Perception & Psychophysics

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“…Most studies have dealt with stimuli that stimulated the first-order motion system (e.g. Burt & Sperling, 1981;Kolers, 1972;Navon, 1976;Papathomas, Gorea & Julesz, 1991; Shechter, Hochstein & Hillman, 1989;Ullman, 1980;Werkhoven, Snippe & Koenderink, 1990a;Werkhoven et al, 1990b) and these data are adequately explained by the first-order motion energy extraction models.…”

Section: Previous Research In Texture-dejined Motionmentioning

confidence: 99%

“…Detailed studies and analysis were recently presented by Chubb and Sperling (1988, b, 1991, Cavanagh et al (1989), Mather (1991), Turano and Pantle (1989), and Victor and Conte (1989).…”

Section: Motion -From-texturementioning

confidence: 99%

“…The velocity vector assigned a given point in space at a given time is obtained by (i) weighting the energy spectrum of each detector by that detector's response, and (ii) finding the plane through the origin of frequency space that absorbs the greatest amount of this locally measured motion energy. Chubb and Sperling (1988, b, 1991 demonstrated broad classes of drift -balanced and microbalanced stimuli that clearly appeared to move but for which even complete knowledge of the energy of all their Fourier components would be useless in deciding whether their motion was to the left or to the right (see also Cavanagh, Arguin & von Griinau, 1989;Lelkens & Koenderink, 1984; Mather, 199 1; Ramachandran, Rau & Vidyasagar, 1973;Turano & Pantle, 1989;Victor & Conte, 1990). Thus first-order motion energy extraction fails completely to account for the perception of motion in drift-balanced stimuli.…”

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The dimensionality of texture-defined motion: a single channel theory

1993

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We examine apparent motion carried by textural properties. The texture stimuli consist of a sequence of grating patches of various spatial frequencies and amplitudes. Phases are randomized between frames to insure that first-order motion mechanisms direct@ applied to stimulus luminance are not systematically engaged. We use ambiguous apparent motion displays in which a heterogeneous motion path defined by alternating patches of texture s (standard) and texture v (variable) competes with a homogeneous motion path defined solely by patches of texture s. Our results support a one-dimensional (single-channel) model of motion-from-texture in which motion strength is computed from a single spatial transformation of the stimulus--an ucfiuity transformation. The value assigned to a point in space-time by this activity transformation is directly proportional to the modulation amplitude of the local texture and inversely proportional to local spatial frequency (within the range of spatial frequencies examined). The activity transformation is modeled as the rectified output of a low-pass spatial filter applied to stimulus contrast. Our data further suggest that the strength of texture-defined motion between a patch of texture s and a patch of texture v is proportional to the product of the activities of s and v. A strongly counterintuitive prediction of this model borne out in our data is that motion between patches of different texture can be stronger than motion between patches of similar texture (e.g. motion between patches of a low contrast, low frequency texture 1 and patches of high contrast, high frequency texture h can be stronger than motion between patches of similar texture h). Second-order motion Motion metamers Motion energy Motion correspondence INTRODUCTION First -order motion extractionDrifting spatiotemporal modulations of various sorts of optical stuff (such as luminance, contrast, texture, binocular disparity, etc.) can induce vivid motion percepts; in each case "something" appears to move from one place to another. This introspective description, however, does not necessarily reflect the underlying processes in human visual motion processing.The study of visual motion extraction mechanisms has traditionally focused on rigidly moving objects, projecting drifting modulations of luminance. Several physiologically plausible computational models have been proposed to extract motion information from drifting luminance modulations. Examples are the gradient detector (see Moulden & Begg, 1986) and the Reichardt or correlator detector (see Reichardt, 1961). These detectors are designed to detect drifting luminance modulations (or their linear transformations) and are therefore called Jirst-order motion extraction mechanisms (Cavanagh & Mather, 1989) Psychophysical experiments (e.g. van Santen & Sperling, 1984; Werkhoven, Snippe dz Koenderink, 1990b) have shown that motion perception of drifting modulations of luminance is well explained by a first-order computation called motion energy extraction. Indeed, most...

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“…Furthermore, colour channels are included to capture complementary chromatic information. Interestingly, evidence from biological systems suggests that they exploit similar complementary feature combination in their visual processing [10,13,15,26,34].…”

Section: Technical Approach 21 Complementary Spacetime Orientation Dmentioning

confidence: 99%

Spacetime Forests with Complementary Features for Dynamic Scene Recognition

Feichtenhofer¹,

Pinz²,

Wildes³

2013

Procedings of the British Machine Vision Conference 2013

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This paper presents spacetime forests defined over complementary spatial and temporal features for recognition of naturally occurring dynamic scenes. The approach improves on the previous state-of-the-art in both classification and execution rates. A particular improvement is with increased robustness to camera motion, where previous approaches have experienced difficulty. There are three key novelties in the approach. First, a novel spacetime descriptor is employed that exploits the complementary nature of spatial and temporal information, as inspired by previous research on the role of orientation features in scene classification. Second, a forest-based classifier is used to learn a multi-class representation of the feature distributions. Third, the video is processed in temporal slices with scale matched preferentially to scene dynamics over camera motion. Slicing allows for temporal alignment to be handled as latent information in the classifier and for efficient, incremental processing. The integrated approach is evaluated empirically on two publically available datasets to document its outstanding performance.

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Two carriers for motion perception: Color and luminance

Cited by 67 publications

References 26 publications

Segregation by color/luminance does not necessarily facilitate motion discrimination in the presence of motion distractors

Segregation by color/luminance does not necessarily facilitate motion discrimination in the presence of motion distractors

The dimensionality of texture-defined motion: a single channel theory

Spacetime Forests with Complementary Features for Dynamic Scene Recognition

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