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In everyday life we encounter a wide range of liquids (e.g., water, custard, toothpaste) with distinctive optical appearances and viscosities. Optical properties (e.g., color, translucency) are physically independent of viscosity, but, based on experience with real liquids, we may associate specific appearances (e.g., water, caramel) with certain viscosities. Conversely, the visual system may discount optical properties, enabling "viscosity constancy" based primarily on the liquid's shape and motion. We investigated whether optical characteristics affect the perception of viscosity and other properties of liquids. We simulated pouring liquids with viscosities ranging from water to molten glass and rendered them with nine different optical characteristics. In Experiment 1, observers (a) adjusted a match stimulus until it had the same perceived viscosity as a test stimulus with different optical properties, and (b) rated six physical properties of the test stimuli (runniness, shininess, sliminess, stickiness, warmth, wetness). We tested moving and static stimuli. In Experiment 2, observers had to associate names with every liquid in the stimulus set. We find that observers' viscosity matches correlated strongly with the true viscosities and that optical properties had almost no effect. However, some ratings of liquid properties did show substantial interactions between viscosity and optical properties. Observers associate liquid names primarily with optical cues, although some materials are associated with a specific viscosity or combination of viscosity and optics. These results suggest viscosity is inferred primarily from shape and motion cues but that optical characteristics influence recognition of specific liquids and inference of other physical properties.

The ability to navigate through crowds of moving people accurately, efficiently, and without causing collisions is essential for our day-to-day lives. Vision provides key information about one’s own self-motion as well as the motions of other people in the crowd. These two types of information (optic flow and biological motion) have each been investigated extensively; however, surprisingly little research has been dedicated to investigating how they are processed when presented concurrently. Here, we showed that patterns of biological motion have a negative impact on visual-heading estimation when people within the crowd move their limbs but do not move through the scene. Conversely, limb motion facilitates heading estimation when walkers move independently through the scene. Interestingly, this facilitation occurs for crowds containing both regular and perturbed depictions of humans, suggesting that it is likely caused by low-level motion cues inherent in the biological motion of other people.

A vast literature exists on human biological motion perception in impoverished displays, e.g., point-light walkers. Less is known about the perception of impoverished biological motion displays in macaques. We trained 3 macaques in the discrimination of facing direction (left versus right) and forward versus backward walking using motion-capture-based locomotion displays (treadmill walking) in which the body features were represented by cylinder-like primitives. The displays did not contain translatory motion. Discriminating forward versus backward locomotion requires motion information while the facing-direction/view task can be solved using motion and/or form. All monkeys required lengthy training to learn the forward-backward task, while the view task was learned more quickly. Once acquired, the discriminations were specific to walking and stimulus format but generalized across actors. Although the view task could be solved using form cues, there was a small impact of motion. Performance in the forward-backward task was highly susceptible to degradations of spatiotemporal stimulus coherence and motion information. These results indicate that rhesus monkeys require extensive training in order to use the intrinsic motion cues related to forward versus backward locomotion and imply that extrapolation of observations concerning human perception of impoverished biological motion displays onto monkey perception needs to be made cautiously.

A series of seven experiments explored search for opaque targets among transparent distractors or vice versa. Static stimuli produced very inefficient search. With moving items, search for an opaque target among transparent distractors was quite efficient while search for transparent targets was less efficient (Experiment 1). Transparent and opaque items differed from each other on the basis of motion cues, luminance cues, and figural cues (e.g., junction type). Motion cues were not sufficient to support efficient search (Experiments 2–5). Violations of the luminance rules of transparency disrupt search (Experiments 3 and 4). Experiment 5 shows that search becomes inefficient if X-junctions are removed. Experiments 6 and 7 show that efficient search survives if X-junctions are occluded. It appears that guidance of attention to an opaque target is guidance based on “cue combination” (M. S. Landy, L. T. Maloney, E. B. Johnston, & M. Young, 1995). Several cues must be present to produce a difference between opaque and transparent surfaces that is adequate to guide attention.

Previous studies have examined the facilitative effects of prior spatial information on target selection for saccadic eye movements. More recently, studies have shown that prior spatial information also influences target selection for smooth pursuit. However, direct comparisons of the effects of prior information on target selection for pursuit and saccades have not been made. To this end, we provided different classes of prior information and measured their effects on target selection for pursuit and saccades. In Experiment 1, we assessed the relative effects of spatial cues (indicating the target stimulus' initial location) and color cues (indicating the target stimulus' color) on eye movement latencies. In Experiment 2, we assessed the effects of motion cues (indicating the target stimulus' direction of motion) in addition to spatial cues. For both pursuit and saccades, we found that spatial cues reduced eye movement latencies more than color cues (Experiment 1). Spatial cues also reduced eye movement latencies more than motion cues (Experiment 2), even for pursuit, despite the fact that stimulus motion is essential for the generation of pursuit eye movements. These results indicate that both pursuit and saccades are affected to a greater degree by spatial information than motion or color information. We suggest that the primacy of spatial information for both pursuit and saccades reflects the importance of spatial attention in selecting the stimulus target for both eye movements.

Experimental investigations of cue combination typically assume that individual cues provide noisy but unbiased sensory information about world properties. However, in numerous instances, including real-world settings, observers systematically misestimate properties of the world from sensory information. Two such instances are the estimation of shape from stereo and motion cues. Bias in single-cue estimates, therefore poses a problem for cue combination if the visual system is to maintain accuracy with respect to the world, particularly because knowledge about the magnitude of bias in individual cues is typically unknown. Here, we show that observers fail to take account of the magnitude of bias in each cue during combination and instead combine cues in proportion to their reliability so as to increase the precision of the combined-cue estimate. This suggests that observers were unaware of the bias in their sensory estimates. Our analysis of cue combination shows that there is a definable range of circumstances in which combining information from biased cues, rather than vetoing one or other cue, can still be beneficial, by reducing error in the final estimate.

For moving targets, bimodal facilitation of reaction time has been observed for motion in the depth plane (C. Cappe, G. Thut, B. Romei, & M. M. Murray, 2009), but it is unclear whether analogous RT facilitation is observed for auditory–visual motion stimuli in the horizontal plane, as perception of horizontal motion relies on very different cues. Here we found that bimodal motion cues resulted in significant RT facilitation at threshold level, which could not be explained using an independent decisions model (race model). Bimodal facilitation was observed at suprathreshold levels when the RTs for suprathreshold unimodal stimuli were roughly equated, and significant RT gains were observed for direction-discrimination tasks with abrupt-onset motion stimuli and with motion preceded by a stationary phase. We found no speeded responses for bimodal signals when a motion signal in one modality was paired with a spatially co-localized stationary signal in the other modality, but faster response times could be explained by statistical facilitation when the motion signals traveled in opposite directions. These results strongly suggest that integration of motion cues led to the speeded bimodal responses. Finally, our results highlight the importance of matching the unimodal reaction times to obtain response facilitation for bimodal motion signals in the linear plane.

We examined what role motion-streak-like form information plays in heading perception. We presented observers with an integrated form and motion display in which random-dot pairs in a 3D cloud were oriented toward one direction on the screen (the form FOE) to form a radial Glass pattern while moving in a different direction in depth (the motion FOE). Observers' heading judgments were strongly biased toward the form FOE direction (weight: 0.78), and this bias decreased with the reduction of the salience of the global form structure in the Glass pattern. At the local level, the orientation of dot pairs in the Glass pattern can affect their perceived motion direction, leading to a shift of the perceived motion FOE direction in optic flow. However, this shift accounted for about half of the total bias. Using the measurements of the shifted motion FOE and the perceived form FOE directions, we found that at the global level, an optimal combination of these two cues could accurately predict the heading bias observed for the integrated display. Our findings support the claim that motion streaks are effective cues for self-motion perception, and humans make optimal use of both form and motion cues for heading perception.

Fast adaptation biases the perceived motion direction of a subsequently presented ambiguous test pattern (R. Kanai & F. A. Verstraten, 2005). Depending on both the duration of the adapting stimulus ( ranging from tens to hundreds of milliseconds) and the duration of the adaptation-test blank interval, the perceived direction of an ambiguous test pattern can be biased towards the same or the opposite direction of the adaptation pattern, resulting in rapid forms of motion priming or motion aftereffect respectively. These findings were obtained employing drifting luminance gratings. Many studies have shown that first-order motion (luminance-defined) and second-order motion (contrast-defined) stimuli are processed by separate mechanisms. We assessed whether these effects also exist within the second-order motion domain. Results show that fast adaptation to second-order motion biases the perceived direction of a subsequently presented second-order ambiguous test pattern with similar time courses to that obtained for first-order motion. To assess whether a single mechanism could account for these results, we ran a cross-order adaptation condition. Results showed little or no transfer between the two motion cues and probes, suggesting a degree of separation between the neural substrates subserving fast adaptation of first- and second-order motion.

One way the visual system estimates object motion during pursuit is to combine estimates of eye velocity and retinal motion. This questions whether observers need direct access to retinal motion during pursuit. We tested this idea by varying the correlation between retinal motion and objective motion in a two-interval speed discrimination task. Responses were classified according to three motion cues: retinal speed (based on measured eye movements), objective speed, and the relative motion between pursuit target and stimulus. In the first experiment, feedback was based on relative motion and this cue fit the response curves best. In the second experiment, simultaneous relative motion was removed but observers still used the sequential relative motion between pursuit target and dot pattern to make their judgements. In a final experiment, feedback was given explicitly on the retinal motion, using online measurements of eye movements. Nevertheless, sequential relative motion still provided the best account of the data. The results suggest that observers do not have direct access to retinal motion when making perceptual judgements about movement during pursuit.

Visually inferring the stiffness of objects is important for many tasks but is challenging because, unlike optical properties (e.g., gloss), mechanical properties do not directly affect image values. Stiffness must be inferred either (a) by recognizing materials and recalling their properties (associative approach) or (b) from shape and motion cues when the material is deformed (estimation approach). Here, we investigated interactions between these two inference types. Participants viewed renderings of unfamiliar shapes with 28 materials (e.g., nickel, wax, cork). In Experiment 1, they viewed nondeformed, static versions of the objects and rated 11 material attributes (e.g., soft, fragile, heavy). The results confirm that the optical materials elicited a wide range of apparent properties. In Experiment 2, using a blue plastic material with intermediate apparent softness, the objects were subjected to physical simulations of 12 shape-transforming processes (e.g., twisting, crushing, stretching). Participants rated softness and extent of deformation. Both correlated with the physical magnitude of deformation. Experiment 3 combined variations in optical cues with shape cues. We find that optical cues completely dominate. Experiment 4 included the entire motion sequence of the deformation, yielding significant contributions of optical as well as motion cues. Our findings suggest participants integrate shape, motion, and optical cues to infer stiffness, with optical cues playing a major role for our range of stimuli.