Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequency-selective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains. In the higher level, the velocity map is interpreted. Although there are many motion interpretation processes, we highlight the recent progress in research on the perception of material (e.g., specular reflection, liquid viscosity) and on animacy perception. We then consider possible linking mechanisms of the two levels and propose intrinsic flow decomposition as the key problem. To provide insights into computational mechanisms of motion perception, in addition to psychophysics and neurosciences, we review machine vision studies seeking to solve similar problems.
When a conventional stereoscopic display is viewed without stereo glasses, image blurs, or 'ghosts', are visible due to the fusion of stereo image pairs. This artifact severely degrades 2D image quality, making it difficult to simultaneously present clear 2D and 3D contents. To overcome this limitation (backward incompatibility), here we propose a novel method to synthesize ghost-free stereoscopic images. Our method gives binocular disparity to a 2D image, and drives human binocular disparity detectors, by the addition of a quadrature-phase pattern that induces spatial subband phase shifts. The disparity-inducer patterns added to the left and right images are identical except for the contrast polarity. Physical fusion of the two images cancels out the disparity-inducer components and makes only the original 2D pattern visible to viewers without glasses. Unlike previous solutions, our method perfectly excludes stereo ghosts without using special hardware. A simple algorithm can transform 3D contents from the conventional stereo format into ours. Furthermore, our method can alter the depth impression of a real object without its being noticed by naked-eye viewers by means of light projection of the disparity-inducer components onto the object's surface. Psychophysical evaluations have confirmed the practical utility of our method.
The flash-lag effect refers to the phenomenon where a flash of a stationary stimulus presented adjacent to a moving stimulus appears to lag behind it. We investigated whether the flash-lag effect affected the tilt aftereffect using two sets of vertical gratings for a flash and a moving stimulus that created a specific orientation when aligned with a specific temporal offset. Our results show that a change in the perceptual appearance of stimuli in the presence of the flash-lag effect had a negligible influence on the tilt aftereffect. These data suggest that the flash-lag effect originates at a different neural processing stage than the early linear processing that presumably mediates the tilt aftereffect.
There are many situations in which virtual objects are presented half-transparently on a background in real time applications. In such cases, we often want to show the object with constant visibility. However, using the conventional alpha blending, visibility of a blended object substantially varies depending on colors, textures, and structures of the background scene. To overcome this problem, we present a framework for blending images based on a subjective metric of visibility. In our method, a blending parameter is locally and adaptively optimized so that visibility of each location achieves the targeted level. To predict visibility of an object blended by an arbitrary parameter, we utilize one of the error visibility metrics that have been developed for image quality assessment. In this study, we demonstrated that the metric we used can linearly predict visibility of a blended pattern on various texture images, and showed that the proposed blending methods can work in practical situations assuming augmented reality.
The flash-drag (FDE) effect refers to the phenomenon in which the position of a stationary flashed object in one location appears shifted in the direction of nearby motion. Over the past decade, it has been debated how bottom-up and top-down processes contribute to this illusion. In this study, we demonstrate that randomly phase-shifting gratings can produce the FDE. In the random motion sequence we used, the FDE inducer (a sinusoidal grating) jumped to a random phase every 125 ms and stood still until the next jump. Because this random sequence could not be tracked attentively, it was impossible for the observer to discern the jump direction at the time of the flash. By sorting the data based on the flash’s onset time relative to each jump time in the random motion sequence, we found that a large FDE with a broad temporal tuning occurred around 50 to 150 ms before the jump and that this effect was not correlated with any other jumps in the past or future. These results suggest that as few as two frames of unpredictable apparent motion can preattentively cause the FDE with a broad temporal tuning.
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