A motion sequence may be represented as a single pattern in x-y-t space; a velocity of motion corresponds to a three-dimensional orientation in this space. Motion sinformation can be extracted by a system that responds to the oriented spatiotemporal energy. We discuss a class of models for human motion mechanisms in which the first stage consists of linear filters that are oriented in space-time and tuned in spatial frequency. The outputs of quadrature pairs of such filters are squared and summed to give a measure of motion energy. These responses are then fed into an opponent stage. Energy models can be built from elements that are consistent with known physiology and psychophysics, and they permit a qualitative understanding of a variety of motion phenomena.

In this paper we develop a computational model of visual masking based on psychophysical data. The model predicts how the presence of one visual pattern affects the detectability of another. The model allows us to choose texture patterns for computer graphics images that hide the effects of faceting, banding, aliasing, noise and other visual artifacts produced by sources of error in graphics algorithms. We demonstrate the utility of the model by choosing a texture pattern to mask faceting artifacts caused by polygonal tesselation of a flat-shaded curved surface. The model predicts how changes in the contrast, spatial frequency, and orientation of the texture pattern, or changes in the tesselation of the surface will alter the masking effect. The model is general and has uses in geometric modeling, realistic image synthesis, scientific visualization, image compression, and image-based rendering.

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This thesis presents a generic and principled solution for optimising the visual complexity of any arbitrary computer-generated virtual environment (VE). This is performed with the ultimate goal of reducing the inherent latencies of current virtual reality (VR) technology. Effectively, we wish to remove extraneous detail from an environment which the user cannot perceive, and thus modulate the graphical complexity of a VE with little or no perceptual artifacts. The work proceeds by investigating contemporary models and theories of visual perception and then applying these to the field of real-time computer graphics. Subsequently, a technique is devised to assess the perceptual content of a computer-generated image in terms of spatial frequency (c/deg), and a model of contrast sensitivity is formulated to describe a user's ability to perceive detail under various conditions in terms of this metric. This allows us to base the level of detail (LOD) of each object in a VE on a measure of ...

A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-tuned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1® MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that h...

We describe a new, computationally simple method for analyzing the dynamics of neuronal spike trains driven by external stimuli. The goal of our method is to test the predictions of simple spike-generating models against extracellularly recorded neuronal responses. Through a new statistic called the power ratio, we distinguish between two broad classes of responses: (1) responses that can be completely characterized by a variable firing rate, (for example, modulated Poisson and gamma spike trains); and (2) responses for which firing rate variations alone are not sufficient to characterize response dynamics (for example, leaky integrate-and-fire spike trains as well as Poisson spike trains with long absolute refractory periods). We show that the responses of many visual neurons in the cat retinal ganglion, cat lateral geniculate nucleus, and macaque primary visual cortex fall into the second class, which

Search for a target defined by a conjunction of movement and form (e.g., an X moving up in a display of intermingled Os moving up and stationary Xs) is parallel. This result is also found if (a) the moving Os and target X move in unpredictable directions so that the moving stimuli do not form a clear perceptual group or (b) the nontarget Xs also move but in a known, different direction from the Os and target X. In contrast, search is slow and serial if the target may be unpredictably among either moving or stationary stimuli. These results suggest that a component of the visual system operates as a movement filter that can direct attention to stimuli with a common movement characteristic. The filtering cue can be moving (vs. stationary), or movement in 1 particular direction. The results do not support the view that attention can only be directed to groups defined by common fate. McLeod, Driver, and Crisp (1988) showed that search for a target defined by a conjunction of movement and form (e.g., an X moving up among an intermingled set of Os moving up and stationary Xs) was parallel (i.e., detection time was independent of the number of nontarget stimuli). This

A neural model of motion perception simulates psychophysical data concerning first-order and second-order motion stimuli, including the reversal of perceived motion direction with distance from the stimulus (\Gamma display), and data about directional judgments as a function of relative spatial phase or spatial and temporal frequency. Many other second-order motion percepts that have been ascribed to a second non-Fourier processing stream can also be explained in the model by interactions between ON and OFF cells within a single, neurobiologically interpreted magnocellular processing stream. Yet other percepts may be traced to interactions between form and motion processing streams, rather than to processing within multiple motion processing streams. The model hereby explains why monkeys with lesions of of the parvocellular layers, but not the magnocellular layers, of the lateral geniculate nucleus (LGN) are capable of detecting the correct direction of second-order motion, why most ce...

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We show that spike timing adds to the information content of spike trains for transiently presented stimuli but not for comparable steady-state stimuli, even if the latter elicit transient responses. Contrast responses of 22 single neurons in macaque V1 to periodic presentation of steady-state stimuli (drifting sinusoidal gratings) and transient stimuli (drifting edges) of optimal spatiotemporal parameters were recorded extracellularly. The responses were analyzed for contrast-dependent clustering in spaces determined by metrics sensitive to the temporal structure of spike trains. Two types of metrics, costbased spike time metrics and metrics based on Fourier harmonics of the response, were used. With both families of metrics, temporal coding of contrast is lacking in responses to drifting sinusoidal gratings of most (simple and complex) V1 A prevailing view of neural coding is that the meaningful signal