Human visual system model

About: Human visual system model is a research topic. Over the lifetime, 8697 publications have been published within this topic receiving 259440 citations.

Neurodevelopment of the visual system in typically developing children.

Abstract: A central question in developmental psychology is how a child acquires knowledge about the surrounding world. Is it important for learning to know what an object represents, before a child knows how to deal with it? Or does a child learn because it is improving haptic skills to act upon an object, to follow its actions and predict how it behaves? Behavioral research investigating such questions distinguished the role of dorsal and ventral visual streams in learning to "know how" and "know what" about objects, but these studies did not unequivocally resolve how these functions mature. Recent functional, structural, and microstructural neuroimaging research has shed a novel light on the normal development of the human visual system, particularly during later stages of child development. This chapter reviews these neuroimaging studies and interrogates them on the question of whether dorsal and ventral visual streams mature at different rates. Structural gray matter properties within the ventral visual stream show prolonged development compared to the dorsal stream, whereas white matter connectivity within dorsal visual stream structures matures later. Functionally specialized areas in the ventral visual stream show increased size during development, whereas parietal dorsal stream areas show increasing activity associated with high-order visual perception. Such results emphasize the importance of neuroimaging techniques for research on visual cognitive development. They suggest that high-order visual functions mature late and that dorsal and ventral visual streams follow different neurodevelopmental trajectories.

Human visual system based objective digital video quality metrics

Abstract: We present a review on human visual system (HVS) based digital video quality metrics. Particularly, three objective video quality metrics are discussed and analyzed in detail because they represent the state-of-the-art of HVS based quality metric research and have been proposed to and verified by VQEG (Video Quality Expert Group) as the candidates of a possible ITU standard. The purpose of the paper is to provide an up-to-date knowledge of the HVS modeling, how the characteristics of the HVS have been incorporated into quality metrics, and the implementation issues of the metrics as well as the directions of future research.

Foveated mean squared error--a novel video quality metric

Abstract: Efficiency of a video coding process, as well as accuracy of an objective video quality evaluation can be significantly improved by introduction of the human visual system (HVS) characteristics. In this paper we analyze one of these characteristics; namely, visual acuity reduction due to the foveated vision and object movements in a video sequence. We propose a new video quality metric called Foveated Mean Squared Error (FMSE) that takes into account a variable resolution of the HVS across the visual field. The highest visual acuity is at the point of fixation that falls into fovea, an area at retina with the highest density of photoreceptors. Visual acuity decreases rapidly for image regions which are further with respect to the fixation point. FMSE also utilizes the effect of additional spatial acuity reduction due to motion in a video sequence. The quality measures calculated by FMSE have shown a high correlation with experimental results obtained by subjective video quality assessment.

The effect of nonlinear human visual system components on performance of a channelized Hotelling observer in structured backgrounds

Abstract: Linear model observers based on statistical decision theory have been used successfully to predict human visual detection of aperiodic signals in a variety of noisy backgrounds. However, some models have included nonlinearities such as a transducer or nonlinear decision rules to handle intrinsic uncertainty. In addition, masking models used to predict human visual detection of signals superimposed on one of two identical backgrounds (masks) usually include a number of nonlinear components in the channels that reflect properties of the firing of cells in the primary visual cortex (V1). The effect of these nonlinearities on the ability of linear model observers to predict human signal detection in real patient structured backgrounds is unknown. We evaluate the effect of including different nonlinear human visual system components into a linear channelized Hotelling observer (CHO) using a signal known exactly but variable (SKEV) task. In particular, we evaluate whether the rank order of two compression algorithms (JPEG versus JPEG 2000) and two compression encoder settings (JPEG 2000 default versus JPEG 2000 optimized) based on model observer signal detection performance in X-ray coronary angiograms is altered by inclusion of nonlinear components. The results show: 1) the simpler linear CHO model observer outperforms CHO model with the nonlinear components; 2) the rank order of model observer performance for the compression algorithms/parameters does not change when the nonlinear components are included. For the present task and images, the results suggest that the addition of the nonlinearities to a channelized Hotelling model may add complexity to the model observers without great impact on rank order evaluation of image processing and/or acquisition algorithms