Embedded foveation image coding

Wang, Zhou; Bovik, Alan C.

doi:10.1109/83.951527

Cited by 174 publications

(8 citation statements)

References 35 publications

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“…Foveated versions of the stimuli were created by using the approach described in ref. 58 . The contrast sensitivity function describing the decline of accuracy with increasing eccentricity is computed aswhich can be used to assign a cut-off frequency at each eccentricity.…”

Section: Methodsmentioning

confidence: 99%

Multi-step planning of eye movements in visual search

Hoppe

Rothkopf

2019

Sci Rep

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The capability of directing gaze to relevant parts in the environment is crucial for our survival. Computational models have proposed quantitative accounts of human gaze selection in a range of visual search tasks. Initially, models suggested that gaze is directed to the locations in a visual scene at which some criterion such as the probability of target location, the reduction of uncertainty or the maximization of reward appear to be maximal. But subsequent studies established, that in some tasks humans instead direct their gaze to locations, such that after the single next look the criterion is expected to become maximal. However, in tasks going beyond a single action, the entire action sequence may determine future rewards thereby necessitating planning beyond a single next gaze shift. While previous empirical studies have suggested that human gaze sequences are planned, quantitative evidence for whether the human visual system is capable of finding optimal eye movement sequences according to probabilistic planning is missing. Here we employ a series of computational models to investigate whether humans are capable of looking ahead more than the next single eye movement. We found clear evidence that subjects’ behavior was better explained by the model of a planning observer compared to a myopic, greedy observer, which selects only a single saccade at a time. In particular, the location of our subjects’ first fixation differed depending on the stimulus and the time available for the search, which was well predicted quantitatively by a probabilistic planning model. Overall, our results are the first evidence that the human visual system’s gaze selection agrees with optimal planning under uncertainty.

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Section: Methodsmentioning

confidence: 99%

Multi-step planning of eye movements in visual search

Hoppe

Rothkopf

2019

Sci Rep

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“…The algorithm for calculating sensitivity, which has been employed to improve image and video coding efficiency, is called foveation. [14][15][16][17] In this research, eyestrain is measured by calculating a user's gaze position and by determining the user's visual information on the basis of foveation. Humans perceive a dramatic decrease in their visual sensitivity in areas away from the point of gaze.…”

Section: Eye Response Measurementmentioning

confidence: 99%

Minimizing eyestrain on a liquid crystal display considering gaze direction and visual field of view

et al. 2013

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Abstract. Recently, it has become necessary to evaluate the performance of display devices in terms of human factors. To meet this requirement, several studies have been conducted to measure the eyestrain of users watching display devices. However, these studies were limited in that they did not consider precise human visual information. Therefore, a new eyestrain measurement method is proposed that uses a liquid crystal display (LCD) to measure a user's gaze direction and visual field of view. Our study is different in the following four ways. First, a user's gaze position is estimated using an eyeglass-type eye-image capturing device. Second, we propose a new eye foveation model based on a wavelet transform, considering the gaze position and the gaze detection error of a user. Third, three video adjustment factors-variance of hue (VH), edge, and motion information-are extracted from the displayed images in which the eye foveation models are applied. Fourth, the relationship between eyestrain and three video adjustment factors is investigated. Experimental results show that the decrement of the VH value in a display induces a decrease in eyestrain. In addition, increased edge and motion components induce a reduction in eyestrain.

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“…In future work, the combination of several deep learning-based features should be studied. In addition, the use of other techniques for incorporating attention, foveation [107] and multi scale analysis can be seen as potential future work. The integration of more viewing distances will also be investigated.…”

Section: Discussionmentioning

confidence: 99%

Image Quality Assessment without Reference by Combining Deep Learning-Based Features and Viewing Distance

Chetouani

Pedersen

2021

Applied Sciences

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An abundance of objective image quality metrics have been introduced in the literature. One important essential aspect that perceived image quality is dependent on is the viewing distance from the observer to the image. We introduce in this study a novel image quality metric able to estimate the quality of a given image without reference for different viewing distances between the image and the observer. We first select relevant patches from the image using saliency information. For each patch, a feature vector is extracted from a convolutional neural network model and concatenated at the viewing distance, for which the quality is predicted. The resulting vector is fed to fully connected layers to predict subjective scores for the considered viewing distance. The proposed method was evaluated using the Colourlab Image Database: Image Quality and Viewing Distance-changed Image Database. Both databases provide subjective scores at two different viewing distances. In the Colourlab Image Database: Image Quality we obtain a Pearson correlation of 0.87 at both 50 cm and 100 cm viewing distances, while in the Viewing Distance-changed Image Database we obtained a Pearson correlation of 0.93 and 0.94 at viewing distance of four and six times the image height. The results show the efficiency of our method and its generalization ability.

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Embedded foveation image coding

Cited by 174 publications

References 35 publications

Multi-step planning of eye movements in visual search

Multi-step planning of eye movements in visual search

Minimizing eyestrain on a liquid crystal display considering gaze direction and visual field of view

Image Quality Assessment without Reference by Combining Deep Learning-Based Features and Viewing Distance

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