Abstract not found

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...

Electrophysiological studies indicate that neurons in the Middle Temporal (MT) area of the primate brain are selective for the velocity of visual stimuli. This paper describes a computational model of MT physiology, in which local image velocities are represented via the distribution of MT neuronal responses. The computation is performed in two stages, corresponding to neurons in cortical areas V1 and MT. Each stage computes a weighted linear sum of inputs, followed by rectification and divisive normalization. V1 receptive field weights are designed for orientation and direction selectivity. MT receptive field weights are designed for velocity (both speed and direction) selectivity. The paper includes computational simulations accounting for a wide range of physiological data, and describes experiments that could be used to further test and refine the model.

The conceptual component of this work is about "reference surfaces" which are the dual of reference frames often used for shape representation purposes. The theoretical component of this work involves the question of whether one can find a unique (and simple) mapping that aligns two arbitrary perspective views of an opaque textured quadric surface in 3D, given (i) few corresponding points in the two views, or (ii) the outline conic of the surface in one view (only) and few corresponding points in the two views. The practical component of this work is concerned with applying the theoretical results as tools for the task of achieving full correspondence between views of arbitrary objects. Short version of this manuscript appears in the Proceedings of ECCV'94, Stockholm, Sweden. Copyright c fl Massachusetts Institute of Technology, 1994 This report describes research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences and at t...

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...

A number of researchers have proposed models of early motion sensing based on direction-selective, spatiotemporal linear operators. Others have formalized the problem of measuring optical flow in terms of the spatial and temporal derivatives of stimulus intensity. Recently, the spatiotemporal filter models and the gradient-based methods have been placed into a common framework. In this chapter, we review that framework and we extend it to develop a new model for the computation and representation of velocity information in the visual system. We use the model to simulate psychophysical data on perceived velocity of sine-grating plaid patterns, and to simulate physiological data on responses of simple cells in primary (striate) visual cortex.

The paper presents a simple model for recovering affine shape and correspondence from two orthographic views of a three-dimensional object. The paper has two parts. In the first part it is shown that four corresponding points along two orthographic views, taken under similar illumination conditions, determine affine shape and correspondence for all other points. In the second part it is shown that the scheme is useful for purposes of visual recognition by generating novel views of an object given two model views in full correspondence and four corresponding points between the model views and the novel view. It is also shown that the scheme can handle objects with smooth boundaries, to a good approximation, without introducing any modifications or additional model views.

We present a method for image interpolation that is able to create high-quality, perceptually convincing transitions between recorded images. By implementing concepts derived from human vision, the problem of a physically correct image interpolation is relaxed to that of image interpolation which is perceived as visually correct by human observers. We find that it suffices to focus on exact edge correspondences, homogeneous regions and coherent motion to compute convincing results. A user study confirms the visual quality of the proposed image interpolation approach. We show how each aspect of our approach increases perceived quality of the result. We compare the results to other methods and assess achievable quality for different types of scenes.

Currently two major limitations to applying vision in real tasks are robustness in realworld, uncontrolled environments, and the computational resources required for real-time operation. In particular, many current robotic visual motion detection algorithms (optical flow) are not suited for practical applications such as segmentation and structure-frommotion because they either require highly specialized hardware or up to several minutes on a scientific workstation. In addition, many such algorithms depend on the computation of first and in some cases higher numerical derivatives, which are notoriously sensitive to noise. In fact the current trend in optical flow research is to stress accuracy under ideal conditions and not to consider computational resource requirements or resistance to noise, which are essential for real-time robotics. As a result robotic vision researchers are frustrated by an inability to obtain reliable optical flow estimates in real-world conditions, and practica...

Lu and Sperling [Vision Res. 35, 2697 (1995)] proposed that human visual motion perception is served by three separate motion systems: a first-order system that responds to moving luminance patterns, a second-order system that responds to moving modulations of feature types—stimuli in which the expected luminance is the same everywhere but an area of higher contrast or of flicker moves, and a third-order system that computes the motion of marked locations in a ‘‘salience map,’ ’ that is, a neural representation of visual space in which the locations of important visual features (‘‘figure’’) are marked and ‘‘ground’ ’ is unmarked. Subsequently, there have been some strongly confirmatory reports: different gain-control mechanisms for first- and second-order motion, selective impairment of first- versus second- and/or third-order motion by different brain injuries, and the classification of new third-order motions, e.g., isoluminant chromatic motion. Various procedures have successfully discriminated between second- and third-order motion (when first-order motion is excluded): dual tasks, second-order reversed phi, motion competition, and selective adaptation. Meanwhile, eight apparent contradictions to the three-systems theory have been proposed. A review and reanalysis here of the new evidence, pro and con, resolves the challenges and yields a more clearly defined and significantly strengthened theory. © 2001 Optical Society of America OCIS codes: 330.4150.