6 research outputs found
Visual Comfort Assessment for Stereoscopic Image Retargeting
In recent years, visual comfort assessment (VCA) for 3D/stereoscopic content
has aroused extensive attention. However, much less work has been done on the
perceptual evaluation of stereoscopic image retargeting. In this paper, we
first build a Stereoscopic Image Retargeting Database (SIRD), which contains
source images and retargeted images produced by four typical stereoscopic
retargeting methods. Then, the subjective experiment is conducted to assess
four aspects of visual distortion, i.e. visual comfort, image quality, depth
quality and the overall quality. Furthermore, we propose a Visual Comfort
Assessment metric for Stereoscopic Image Retargeting (VCA-SIR). Based on the
characteristics of stereoscopic retargeted images, the proposed model
introduces novel features like disparity range, boundary disparity as well as
disparity intensity distribution into the assessment model. Experimental
results demonstrate that VCA-SIR can achieve high consistency with subjective
perception
No-Reference Quality Assessment for 360-degree Images by Analysis of Multi-frequency Information and Local-global Naturalness
360-degree/omnidirectional images (OIs) have achieved remarkable attentions
due to the increasing applications of virtual reality (VR). Compared to
conventional 2D images, OIs can provide more immersive experience to consumers,
benefitting from the higher resolution and plentiful field of views (FoVs).
Moreover, observing OIs is usually in the head mounted display (HMD) without
references. Therefore, an efficient blind quality assessment method, which is
specifically designed for 360-degree images, is urgently desired. In this
paper, motivated by the characteristics of the human visual system (HVS) and
the viewing process of VR visual contents, we propose a novel and effective
no-reference omnidirectional image quality assessment (NR OIQA) algorithm by
Multi-Frequency Information and Local-Global Naturalness (MFILGN).
Specifically, inspired by the frequency-dependent property of visual cortex, we
first decompose the projected equirectangular projection (ERP) maps into
wavelet subbands. Then, the entropy intensities of low and high frequency
subbands are exploited to measure the multi-frequency information of OIs.
Besides, except for considering the global naturalness of ERP maps, owing to
the browsed FoVs, we extract the natural scene statistics features from each
viewport image as the measure of local naturalness. With the proposed
multi-frequency information measurement and local-global naturalness
measurement, we utilize support vector regression as the final image quality
regressor to train the quality evaluation model from visual quality-related
features to human ratings. To our knowledge, the proposed model is the first
no-reference quality assessment method for 360-degreee images that combines
multi-frequency information and image naturalness. Experimental results on two
publicly available OIQA databases demonstrate that our proposed MFILGN
outperforms state-of-the-art approaches
Biosignalų požymių regos diskomfortui vertinti išskyrimas ir tyrimas
Comfortable stereoscopic perception continues to be an essential area of research. The growing interest in virtual reality content and increasing market for head-mounted displays (HMDs) still cause issues of balancing depth perception and comfortable viewing. Stereoscopic views are stimulating binocular cues – one type of several available human visual depth cues which becomes conflicting cues when stereoscopic displays are used. Depth perception by binocular cues is based on matching of image features from one retina with corresponding features from the second retina. It is known that our eyes can tolerate small amounts of retinal defocus, which is also known as Depth of Focus. When magnitudes are larger, a problem of visual discomfort arises.
The research object of the doctoral dissertation is a visual discomfort level. This work aimed at the objective evaluation of visual discomfort, based on physiological signals. Different levels of disparity and the number of details in stereoscopic views in some cases make it difficult to find the focus point for comfortable depth perception quickly. During this investigation, a tendency for differences in single sensor-based electroencephalographic EEG signal activity at specific frequencies was found. Additionally, changes in eye tracker collected gaze signals were also found. A dataset of EEG and gaze signal records from 28 control subjects was collected and used for further evaluation.
The dissertation consists of an introduction, three chapters and general conclusions. The first chapter reveals the fundamental knowledge ways of measuring visual discomfort based on objective and subjective methods. In the second chapter theoretical research results are presented. This research was aimed to investigate methods which use physiological signals to detect changes on the level of sense of presence. Results of the experimental research are presented in the third chapter. This research aimed to find differences in collected physiological signals when a level of visual discomfort changes. An experiment with 28 control subjects was conducted to collect these signals.
The results of the thesis were published in six scientific publications – three in peer-reviewed scientific papers, three in conference proceedings. Additionally, the results of the research were presented in 8 conferences.Dissertatio
Visual comfort assessment for stereoscopic image retargeting
In recent years, visual comfort assessment (VCA) for 3D/stereoscopic content has aroused extensive attention. However, much less work has been done on the perceptual evaluation of stereoscopic image retargeting. In this paper, we first build a Stereoscopic Image Retargeting Database (SIRD), which contains source images and retargeted images produced by four typical stereoscopic retargeting methods. Then, the subjective experiment is conducted to assess four aspects of visual distortion, i.e. visual comfort, image quality, depth quality and the overall quality. Furthermore, we propose a Visual Comfort Assessment metric for Stereoscopic Image Retargeting (VCA-SIR). Based on the characteristics of stereoscopic retargeted images, the proposed model introduces novel features like disparity range, boundary disparity as well as disparity intensity distribution into the assessment model. Experimental results demonstrate that VCA-SIR can achieve high consistency with subjective perception