TOWARDS A DESCRIPTIVE DEPTH INDEX FOR 3D CONTENT: MEASURING PERSPECTIVE DEPTH CUES

International audience3D quality of experience (QoE) in nature is a multidimensional problem and involves many factors that contribute to the global quality rating such as image quality, depth perception and visual discomfort. One important aspect for the development and evaluation of 3D processing techniques is the selection of appropriate 3D content. To this aim it is necessary to develop computational methods that can automatically measure the 3D characteristics of a scene, similar to the spatial and temporal information indices commonly used for assessing 2D content. The presented work is one step in the development of such a depth index (DI) which will target the evaluation of the depth-related characteristics of 3D video sequences. The paper focuses on the linear perspective as one of the major monocular depth cues. It compares two distinct approaches for measuring the strength of perspective depth cues and analyzes their limits on a 2D image dataset with associated subjective ratings

3D Quality is More Than Just the Sum of 2D And Depth

The success of 3DTV, as one of the emerging multimedia formats, will largely depend on the quality of experience it provides to the viewer in relation to traditional media. Therefore reliable methods for quality assessment are crucial in order to optimize 3D systems and services. The goal of this paper is to review recent developments in 3D quality assessment and discuss future directions in this young research fields

Geotag propagation in social networks based on user trust model

In the past few years sharing photos within social networks has become very popular. In order to make these huge collections easier to explore, images are usually tagged with representative keywords such as persons, events, objects, and locations. In order to speed up the time consuming tag annotation process, tags can be propagated based on the similarity between image content and context. In this paper, we present a system for efficient geotag propagation based on a combination of object duplicate detection and user trust modeling. The geotags are propagated by training a graph based object model for each of the landmarks on a small tagged image set and finding its duplicates within a large untagged image set. Based on the established correspondences between these two image sets and the reliability of the user, tags are propagated from the tagged to the untagged images. The user trust modeling reduces the risk of propagating wrong tags caused by spamming or faulty annotation. The effectiveness of the proposed method is demonstrated through a set of experiments on an image database containing various landmark

Temporal Synchronization in Stereoscopic Video: Influence on Quality of Experience and Automatic Asynchrony Detection

In this paper, we analyze the influence of temporal asyn- chrony on the subjective quality of stereoscopic video. Based on our recently created 3D video database, different levels of asynchrony were simulated and a comprehensive subjective test was conducted to determine the associated degrada- tions in quality of experience. Furthermore, we developed a method to detect asynchrony between left and right video streams based on canonical correlation analysis. Experiments demonstrate the robustness of this method with respect to different amounts of asynchrony and scene depth, which makes it suitable to predict quality of experience or automatic resynchronization

A new analysis method for paired comparison and its application to 3D quality assessment

Among various subjective quality evaluation methodologies, paired comparison has the advantage of improved simplicity of the subjects’ evaluation task due to simplified rating scales and direct comparison of two stimuli. Thus, it may lead to more reliable results when individual quality levels are difficult to define, quality differences between stimuli are small or multiple quality factors are involved. This paper proposes a new method to analyze results of paired comparison-based subjective tests. By assuming that ties convey information about significant differences between two stimuli being compared, the confidence intervals for the quality scores are estimated using a maximum likelihood criterion, which enables us to intuitively examine the significance of quality score differences. We describe the complete test methodology including the test procedure, outlier detection and score analysis applied to quality assessment of 3D images acquired using varying camera distances. Experimental results demonstrate the usefulness of the proposed analysis method, as well as the enhanced quality discriminability of the paired comparison methodology in comparison to the conventional single stimulus methodology

Paired comparison-based subjective quality assessment of stereoscopic images

As 3D image and video content has gained significant popularity, subjective 3D quality assessment has become an important issue for the creation, processing, and distribution of high quality 3D content. Reliable subjective quality assessment of 3D content is often difficult due to the subjects’ limited 3D experience, the interaction of multiple quality factors, minor quality differences between stimuli, etc. Among subjective evaluation methodologies, paired comparison has the advantage of improved simplicity and reliability, which can be useful to tackle the aforementioned difficulties. In this paper, we propose a new method to analyze the results of paired comparison-based subjective tests. We assume that ties convey information about the significance of quality score differences between two stimuli. Then, a maximum likelihood estimation is performed to obtain confidence intervals providing intuitive measures of significance of the quality differences. We describe the complete test procedure using the proposed method, from subjective experiment design to outlier detection and score analysis for 3D image quality assessment. Especially, we design the test procedure in a way that quality comparison across different contents is enabled while the number of pair-wise comparisons is minimized. Experimental results on a stereoscopic image database with varying camera distances demonstrate the usefulness of the proposed method and enhanced quality discriminability of paired comparison in comparison to the conventional single stimulus methodology

Social game Epitome versus automatic visual analysis

With the rapid growth of digital photography, sharing of photos with friends and family has become very popular. When people share their photos, they usually organize them in albums according to events or places. To tell the story of some important events in one's life, it is desirable to have an efficient summarization tool which can help people to get a quick overview of an album containing huge number of photos. In this paper, we analyze an approach for photo album summarization through a novel social game "Epitome'" as a Facebook application. This social game can collect research data and, at the same time, it provides a collage or a cover photo of the user's photo album, while, at the same time, the user enjoys playing the game. As a benchmark comparison to this game, we performed automatic visual analysis considering several state-of-the-art features

Multimodal Person Search Combining Information Fusion and Relevance Feedback

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