. In part I of this article a correlation based model for the developmental process of spatiotemporal receptive fields has been introduced. In this model the development is described as an activity-dependent competition between four types of input from the lateral geniculate nucleus onto a cortical cell, viz. non-lagged ON and OFF and lagged ON and OFF inputs. In the present paper simulation results and a first analysis are presented for this model. We study the developmental process both before and after eye-opening and compare the results with experimental data from reverse correlation measurements. The outcome of the developmental process is determined mainly by the spatial and the temporal correlations between the different inputs. In particular, if the mean correlation between non-lagged and lagged inputs is weak, receptive fields with a widely varying degree of direction selectivity emerge. However, spatiotemporal receptive fields may show rotation of their preferred orientation ...

The perceived direction of a grating moving behind an elongated aperture is biased towards the aperture’s long axis. This “barber pole ” illusion is a consequence of integrating one-dimensional (1D) or grating and two-dimensional (2D) or terminator motion signals. In humans, we recorded the ocular following responses to this stimulus. Tracking was always initiated at ultra-short latencies ( � 85 ms) in the direction of grating motion. With elongated apertures, a later component was initiated 15–20 ms later in the direction of the terminator motion signals along the aperture’s long axis. Amplitude of the later component was dependent upon the aperture’s aspect ratio. Mean tracking direction at the end of the trial (135–175 ms after stimulus onset) was between the directions of the vector sum computed by integrating either terminator motion signals only or both grating and terminator motion signals. Introducing an elongated mask at the center of the “barber pole ” did not affect the latency difference between early and later components, indicating that this latency shift was not due to foveal versus peripheral locations of 1D and 2D motion signals. Increasing the size of the foveal mask up to 90 % of the stimulus area selectively reduced the strength of the grating motion signals and, consequently, the amplitude of the early component. Conversely, reducing the contrast of, or indenting the aperture’s edges, selectively reduced the strength of terminator motion signals and, consequently, the amplitude of the later component. Latencies were never affected by these manipulations. These results tease

A segmentation method based on the integration of motion and brightness is proposed for image sequences. The method is composed of two parallel pathways that process motion and brightness, respectively. Inspired by the visual system, the motion pathway has two stages. The first stage estimates local motion at locations with reliable information. The second stage performs segmentation based on local motion estimates. In the brightness pathway, the input scene is segmented into regions based on brightness distribution. Subsequently, segmentation results from the two pathways are integrated to refine motion estimates. The final segmentation is performed in the motion network based on refined estimates. For segmentation, locally excitatory globally inhibitory oscillator network (LEGION) architecture is employed whereby the oscillators corresponding to a region of similar motion/brightness oscillate in synchrony and different regions attain different phases. Results on synthetic and real im...

Extrastriate cortical area MT is thought to process behaviorally important visual motion signals. Psychophysical studies suggest that visual motion signals may be analyzed by multiple mechanisms, a “first-order ” one based on luminance, and a “second-order ” one based upon higher level cues (e.g. contrast, flicker). Second-order motion is visible to human observers, but should be invisible to first-order motion sensors. To learn if area MT is involved in the analysis of second-order motion, we measured responses to first- and second-order gratings of single neurons in area MT (and in one experiment, in area V1) in anesthetized, paralyzed macaque monkeys. For each neuron, we measured directional and spatio-temporal tuning with conventional first-order gratings and with second-order gratings created by spatial modulation of the flicker rate of a random texture. A minority of MT and V1 neurons exhibited significant selectivity for direction or orientation of second-order gratings. In nearly all cells, response to second-order motion was weaker than response to first-order motion. MT cells with significant selectivity for second-order motion tended to be more responsive and more sensitive to luminance contrast, but were in other respects similar to the remaining MT neurons; they did not appear to represent a distinct subpopulation. For those cells selective for second-order motion, we found a correlation between the preferred directions of first- and second-order motion, and weak correlations in preferred spatial frequency. These cells preferred lower temporal

In this paper, some image registration algorithms are investigated for the purpose of image fusion in a digital camera application. A hybrid scheme which uses both feature-based and intensity-based methods is proposed. In particular, an edge-based image registration approach is developed to guide the intensity-based registration which uses optical flow estimation. The idea of coarse-to-fine multi-scale iterative refinement is also utilized. The combination of these different methods tends to compensate for any deficiencies in the individual methods. Experiments show that our approach provides accurate registrations for the digital camera application. It is also demonstrated that the approach proves useful for registering some multi-spectral images. Keywords-Image fusion, registration, multi-scale, optical flow, feature-based. Tel. 610-758-4909, email: zhz3@lehigh.edu y Tel. 610-758-3459, FAX: 610-758-6279, email: rblum@eecs.lehigh.edu (contact author) z This research was supporte...

tive Vision and especially Prof. Ruzena Bajcsy, Henrik Christianssen, Prof. Jim Crowley, Prof. Randal Nelson and Prof. Giulio Sandini were most useful in the development of my ideas. The help of Kourosh Pahlavan and Prof. Jan-Olof Eklundh in gathering image data with the KTH-head is highly appreciated. Especially I would like to thank my family, Willibald and Dietlinde, Barbara, Elke, Wolfgang and Magdalena for their love and support throughout the years. This work would not have been possible without the generous support of the Osterreichisches Bundesministerium fur Wissenschaft und Forschung, the Osterreichische Bundekammer der Gewerblichen Wirtschaft and the Directorate of Robotics and Machine Intelligence of the National Science Foundation. i Contents 1 Introduction 1 1.1 Classical computer vision : : : : : : : : : : : : : : : : : : : : : : : : : : : 2 1.2 The state of the art : : : : : : : : : : : : : : : : : : : : : : : : : : :

wo speeds, but each speed was generated by a range of spatial and temporal displacements. Once more, subjects saw two surfaces and precisely judged the speed of the slower surface, demonstrating that segregation may be based solely on differences in local speed. We conclude that the visual system calculates two speed signals, one speed signal is coarse, local and used for segregation and the second signal is precise, global and used for speed discrimination. Human psychophysics Local velocity Speed discrimination Motion transparency INTRODUCTION Human observers can judge an object's velocity with remarkable precision: under optimal conditions observers can detect a 5% difference in the speed, and a 1 deg difference in the direction of two moving objects (McKee, 1981; McKee, Silverman & Nakayama, 1986; Levinson & Sekuler, 1976; Watamaniuk & Duchon, 1992; Watamaniuk & Sekuler, 1992). Although much research has focused on this remarkable aspect of visual function, it is still uncl

Quality assessment plays a very important role in almost all aspects of multimedia signal processing such as acquisition, coding, display, processing etc. Several objective quality metrics have been proposed for images, but video quality assessment has received relatively little attention. Most of the video quality metrics in the literature are simple extensions of metrics for images. In this paper, we integrate natural image statistics and the theory of optical flow to propose a new model for the statistics of video signals in the wavelet domain. This model utilizes motion information in video sequences, which is the main difference in moving from images to video. Results are presented to demonstrate the effectiveness of this model to describe the statistics of wavelet coefficients. We then briefly describe how this model can be used in an information theoretic framework to develop quality metrics for video sequences. 1.

The perceived direction of a grating moving behind an elongated aperture is biased towards the aperture's long axis.

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