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To address the issues of viewing safety in stereoscopic three-dimensional television, it is important to investigate determinants of visual discomfort in viewing stereoscopic images. In stereoscopic viewing, it is well known that visual discomfort can be induced by excessive binocular disparity, fast changes in binocular disparity, and binocular asymmetry. However, subjective sensation of visual discomfort could also be substantially different depending on other characteristics of visual stimulus given the complexity of the visual system. From previous studies that have investigated the relation between stimulus characteristics and binocular fusion limit, we speculate that stimulus width (i.e., object width in the stereoscopic scene) can also affect the perceived visual discomfort of stereoscopic images. This paper investigates the effect of stimulus width on visual discomfort by measuring subjective visual discomfort and binocular fusion time. Experimental results show that smaller stimulus width could induce more visual discomfort and increase binocular fusion time.

This paper proposes object-dependent disparity features to predict the visual discomfort in stereoscopic 3-D images. The proposed object-dependent disparity features quantify the level of visual comfort influenced by disparity gradient of nearby objects and object width, respectively. They consist of relative disparity (mean of disparity difference between nearby objects) and object thickness (ratio of mean width to mean absolute disparity of an object). The prediction performance of the proposed disparity features is evaluated using various types of stereoscopic images. Experimental results demonstrate that the combined use of the proposed object-dependent disparity features substantially improve the prediction performance of the conventional disparity magnitude- and spatial complexity-related features. The performance gain ranges from 0.045 to 0.135 of correlation coefficient, compared with the feature combinations used in the conventional visual comfort metrics.

Universal Multimedia Access (UMA) aims at enabling a straightforward consumption of multimedia content in heterogeneous usage environments. These usage environments may range from mobile devices in a wireless network to high-end desktop computers with wired network connectivity. Scalable video content can be used to deal with the restrictions and capabilities of diverse usage environments. However, in order to optimally tailor scalable video content along the temporal, spatial, or perceptual quality axis, a metric is needed that reliably models subjective video quality. The major contribution of this paper is the development of a novel full-reference quality metric for scalable video bit streams that are compliant with the H.264/AVC Scalable Video Coding (SVC) standard. The scalable video bit streams are intended to be used in mobile usage environments (e.g., adaptive video streaming to mobile devices). The proposed quality metric allows modeling the temporal, spatial, and perceptual quality characteristics of SVC-compliant bit streams by taking into account several properties of the compressed bit streams. These properties include the temporal and spatial variance of the video content, the frame rate, the spatial resolution, and PSNR values. An extensive number of subjective experiments have been conducted to construct and validate our quality metric. Experimental results show that the average correlation coefficient for the video sequences tested is as high as 0.95 (compared to a value of 0.60 when only using the traditional PSNR quality metric). The proposed quality metric also shows a performance that is a uniformly high for video sequences with different temporal and spatial characteristics.