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.

System and method for automatically learning flexible sprites in video layers

Abstract: A simplified general model and an associated estimation algorithm is provided for modeling visual data such as a video sequence. Specifically, images or frames in a video sequence are represented as collections of flat moving objects that change their appearance and shape over time, and can occlude each other over time. A statistical generative model is defined for generating such visual data where parameters such as appearance bit maps and noise, shape bit-maps and variability in shape, etc., are known. Further, when unknown, these parameters are estimated from visual data without prior pre-processing by using a maximization algorithm. By parameter estimation and inference in the model, visual data is segmented into components which facilitates sophisticated applications in video or image editing, such as, for example, object removal or insertion, tracking and visual surveillance, video browsing, photo organization, video compositing, etc.

Perceptually-guided foveation for light field displays

Abstract: A variety of applications such as virtual reality and immersive cinema require high image quality, low rendering latency, and consistent depth cues. 4D light field displays support focus accommodation, but are more costly to render than 2D images, resulting in higher latency.The human visual system can resolve higher spatial frequencies in the fovea than in the periphery. This property has been harnessed by recent 2D foveated rendering methods to reduce computation cost while maintaining perceptual quality. Inspired by this, we present foveated 4D light fields by investigating their effects on 3D depth perception. Based on our psychophysical experiments and theoretical analysis on visual and display bandwidths, we formulate a content-adaptive importance model in the 4D ray space. We verify our method by building a prototype light field display that can render only 16% -- 30% rays without compromising perceptual quality.

Efficient underwater image and video enhancement based on Retinex

Abstract: The Retinex models the human visual system to perceive natural colors, which could improve the contrast and sharpness of the degraded image and also provide color constancy and dynamic range simultaneously. This endows the Retinex exceeding advantages for enhancing the underwater image. Based on the multi-scale Retinex, an efficient enhancement method for underwater image and video is presented in this paper. Firstly, the image is pre-corrected to equalize the pixel distribution and reduce the dominating color. Then, the classical multi-scale Retinex with intensity channel is applied to the pre-corrected images for further improving the contrast and the color. In addition, multi-down-sampling and infinite impulse response Gaussian filtering are adopted to increase processing speed. Subsequently, the image is restored from logarithmic domain and the illumination of the restored image is compensated based on statistical properties. Finally, the color is selectively preserved by the inverted gray world method depending on imaging conditions and application requirements. Five kinds of typical underwater images with green, blue, turbid, dark and colorful backgrounds and two underwater videos are enhanced and evaluated on Jetson TX2, respectively, to verify the effectiveness of the proposed method.

What your visual system sees where you are not looking

Abstract: What is the representation in early vision? Considerable research has demonstrated that the representation is not equally faithful throughout the visual field; representation appears to be coarser in peripheral and unattended vision, perhaps as a strategy for dealing with an information bottleneck in visual processing In the last few years, a convergence of evidence has suggested that in peripheral and unattended regions, the information available consists of local summary statistics Given a rich set of these statistics, many attributes of a pattern may be perceived, yet precise location and configuration information is lost in favor of the statistical summary This representation impacts a wide range of visual tasks, including peripheral identification, visual search, and visual cognition of complex displays This paper discusses the implications for understanding visual perception, as well as for imaging applications such as information visualization