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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.


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Proceedings ArticleDOI
TL;DR: This work proposes models for typical distortions encountered in video compression/transmission applications, and derives a multi-scale weighted variant of the complex wavelet SSIM (WCWSSIM), with weights based on the human contrast sensitivity function to handle local mean shift distortions.
Abstract: Perceptual image quality metrics have explicitly accounted for human visual system (HVS) sensitivity to subband noise by estimating thresholds above which distortion is just-noticeable. A recently proposed class of quality metrics, known as structural similarity (SSIM), models perception implicitly by taking into account the fact that the HVS is adapted for extracting structural information (relative spatial covariance) from images. We compare specific SSIM implementations both in the image space and the wavelet domain. We also evaluate the effectiveness of the complex wavelet SSIM (CWSSIM), a translation-insensitive SSIM implementation, in the context of realistic distortions that arise from compression and error concealment in video transmission applications. In order to better explore the space of distortions, we propose models for typical distortions encountered in video compression/transmission applications. We also derive a multi-scale weighted variant of the complex wavelet SSIM (WCWSSIM), with weights based on the human contrast sensitivity function to handle local mean shift distortions.

84 citations

Journal ArticleDOI
TL;DR: Experiments were conducted in order to determine whether the human visual system is sensitive to the orientational uniformity of otherwise nonuniform point-pair elements and to their midpoint collinearity, and indicate that there are three processes involved in the perception of bilaterally symmetric dot textures.
Abstract: If a random-dot texture is reflected about a given axis, the resulting bilateral symmetry is immediately detected. In order to account for this ability, it has been suggested that the visual system detects reflection in these dot textures because of the existence of a symmetric neural organization, centered about the fovea, which performs a point-by-point analysis. As yet, there is no evidence of such an organization in the human visual system. An alternative description of a bilaterally symmetric texture, that of a two-dimensional distribution of uniformly oriented point-pair elements, of nonuniform size and with collinear midpoints, is more consistent with known mammalian visual-system neurophysiology. Experiments were conducted in order to determine whether the human visual system is sensitive to the orientational uniformity of otherwise nonuniform point-pair elements and to their midpoint collinearity. The results indicate that there are three processes involved in the perception of bilaterally symmetric dot textures: the detection of orientational uniformity of the different sized point-pair elements; the fusion of salient element point-pairs into a salient feature; the detection of the symmetry of the resulting feature. This component-process hypothesis eliminates the necessity to postulate the existence of a symmetrical neural organization centered about the fovea.

84 citations

Proceedings ArticleDOI
05 Aug 2007
TL;DR: It is proposed that the ability of humans to perceive a previously unseen 3D object from a single sketch is based on simple 2D-3D geometrical correlations that are learned from visual experience, and a completely automatic conversion of a single freehand sketch into a physical solid object is demonstrated.
Abstract: We propose a new approach for reconstructing a three-dimensional object from a single two-dimensional freehand line drawing depicting it. A sketch is essentially a noisy projection of a 3D object onto an arbitrary 2D plane. Reconstruction is the inverse projection of the sketched geometry from two dimensions back into three dimensions. While humans can do this reverse-projection remarkably easily and almost without being aware of it, this process is mathematically indeterminate and is very difficult to emulate computationally. Here we propose that the ability of humans to perceive a previously unseen 3D object from a single sketch is based on simple 2D-3D geometrical correlations that are learned from visual experience. We demonstrate how a simple correlation system that is exposed to many object-sketch pairs eventually learns to perform the inverse projection successfully for unseen objects. Conversely, we show how the same correlation data can be used to gauge the understandability of synthetically generated projections of given 3D objects. Using these principles we demonstrate for the first time a completely automatic conversion of a single freehand sketch into a physical solid object. These results have implications for bidirectional human-computer communication of 3D graphic concepts, and might also shed light on the human visual system.

84 citations

Proceedings ArticleDOI
31 Jul 2002
TL;DR: In this paper, the connection between numerical and visual phenomena is investigated, and it is shown that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data.
Abstract: The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerical and visual phenomena. Specifically the questions explored are: (1) Is there a well-defined consistent statistical character associated with good visual representations? (2) Does there exist an ideal visual image? And (3) what are its statistical properties?© (2002) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

84 citations

Journal ArticleDOI
TL;DR: An overview of perceptual based approaches for image enhancement, segmentation and coding, and a brief review of image quality assessment methods, which are used to evaluate the performance of visual information processing techniques.
Abstract: Perceptual approaches have been widely used in many areas of visual information processing. This paper presents an overview of perceptual based approaches for image enhancement, segmentation and coding. The paper also provides a brief review of image quality assessment (IQA) methods, which are used to evaluate the performance of visual information processing techniques. The intent of this paper is not to review all the relevant works that have appeared in the literature, but rather to focus on few topics that have been extensively researched and developed over the past few decades. The goal is to present a perspective as broad as possible on this actively evolving domain due to relevant advances in vision research and signal processing. Therefore, for each topic, we identify the main contributions of perceptual approaches and their limitations, and outline how perceptual vision has influenced current state-of-the-art techniques in image enhancement, segmentation, coding and visual information quality assessment.

84 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202349
202294
2021279
2020311
2019351
2018348