Pedro Rosas

Texture and object motion in slant discrimination: Failure of reliability-based weighting of cues may be evidence for strong fusion

Different types of texture produce differences in slant-discrimination performance (P. Rosas, F. A. Wichmann, & J. Wagemans, 2004). Under the assumption that the visual system is sensitive to the reliability of different depth cues (M. O. Ernst & M. S. Banks, 2002; L. T. Maloney & M. S. Landy, 1989), it follows that the texture type should affect the influence of the texture cue in depth-cue combination. We tested this prediction by combining different texture types with object motion in a slant-discrimination task in two experiments. First, we used consistent cues to observe whether our subjects behaved as linearly combining independent estimates from texture and motion in a statistical optimal fashion (M. O. Ernst & M. S. Banks, 2002). Only 4% of our results were consistent with such an optimal combination of uncorrelated estimates, whereas about 46% of the data were consistent with an optimal combination of correlated estimates from cues. Second, we measured the weights for the texture and motion cues using perturbation analysis. The results showed a large influence of the motion cue and an increasing weight for the texture cue for larger slants. However, in general, the texture weights did not follow the reliability of the textures. Finally, we fitted the correlation coefficients of estimates individually for each texture, motion condition, and observer. This allows us to fit our data from both experiments to an optimal cue combination model with correlated estimates, but inspection of the fitted parameters shows no clear, psychophysically interpretable pattern. Furthermore, the fitted motion thresholds as a function of texture type are correlated with the slant thresholds as a function of texture type. One interpretation of such a finding is a strong coupling of cues.

Texture and haptic cues in slant discrimination: Reliability-based cue weighting without statistically optimal cue combination

A number of models of depth-cue combination suggest that the final depth percept results from a weighted average of independent depth estimates based on the different cues available. The weight of each cue in such an average is thought to depend on the reliability of each cue. In principle, such a depth estimation could be statistically optimal in the sense of producing the minimum-variance unbiased estimator that can be constructed from the available information. Here we test such models by using visual and haptic depth information. Different texture types produce differences in slant-discrimination performance, thus providing a means for testing a reliability-sensitive cue-combination model with texture as one of the cues to slant. Our results show that the weights for the cues were generally sensitive to their reliability but fell short of statistically optimal combination--we find reliability-based reweighting but not statistically optimal cue combination.

The influence of motion coherence manipulations on the synchronization level of a perception-action task.

The present experiment was conducted to examine the integration of the motion coherence paradigm in a synchronization task. Random-dot kinematograms were used to generate a pattern of oscillating dots representing four different coherence levels (10%, 30%, 50% and 100%) and one target-alone condition. The participants had to synchronize their arm with the coherently moving dots according to two different synchronization modes (in-phase and anti-phase). The results revealed a substantial performance decline when the target/noise ratio dropped under the critical threshold situated around the 30% coherence level, albeit independent of the synchronization mode. In general, these findings highlighted the impact of the perception of motion based on the level of motion coherence in the visual signal on the synchronization behavior in a perception-action setting.

Texture and haptic cues in slant discrimination

In vision science the currently most popular models for depth perception are weak fusion models in which the final depth estimate results from a weighted average of the independent depth estimates obtained from each cue [2]. In these models a more reliable cue has a larger weight in the combined estimate. Furthermore, recent studies report that human observes combine depth cues as to obtain the minimal variance unbiased estimator of depth [1]. Different texture types can elicit different performance in a slant discrimination task [3]. In the present study we ask whether the reliability-sensitive weighting is observed in slant discrimination based on texture and haptic cues, when interchanging the texture type on the stimuli (see figure below). In the first experiment, with texture and haptic cues depicting slant consistently, we tested a minimal variance unbiased estimator of slant. That is, whether performance for the haptic and texture cues combined followed: