Video quality

About: Video quality is a research topic. Over the lifetime, 13143 publications have been published within this topic receiving 178307 citations.

Intimacy in long-distance relationships over video chat

Abstract: Many couples live a portion of their lives in a long-distance relationship (LDR). This includes a large number of dating college students as well as couples who are geographically-separated because of situational demands such as work. We conducted interviews with individuals in LDRs to understand how they make use of video chat systems to maintain their relationships. In particular, we have investigated how couples use video to "hang out" together and engage in activities over extended periods of time. Our results show that regardless of the relationship situation, video chat affords a unique opportunity for couples to share presence over distance, which in turn provides intimacy. While beneficial, couples still face challenges in using video chat, including contextual (e.g., location of partners, time zones), technical (e.g., mobility, audio/video quality, networking), and personal (e.g., a lack of physicality needed by most for intimate sexual acts) challenges.

ViS3: an algorithm for video quality assessment via analysis of spatial and spatiotemporal slices

Abstract: Algorithms for video quality assessment (VQA) aim to estimate the qualities of videos in a manner that agrees with human judgments of quality. Modern VQA algorithms often estimate video quality by comparing localized space-time regions or groups of frames from the reference and distorted videos, using comparisons based on visual features, statistics, and/or perceptual models. We present a VQA algorithm that estimates quality via separate estimates of perceived degradation due to (1) spatial distortion and (2) joint spatial and temporal distortion. The first stage of the algorithm estimates perceived quality degradation due to spatial distortion; this stage operates by adaptively applying to groups of spatial video frames the two strategies from the most apparent distortion algorithm with an extension to account for temporal masking. The second stage of the algorithm estimates perceived quality degradation due to joint spatial and temporal distortion; this stage operates by measuring the dissimilarity between the reference and distorted videos represented in terms of two-dimensional spatiotemporal slices. Finally, the estimates obtained from the two stages are combined to yield an overall estimate of perceived quality degradation. Testing on various video-quality databases demonstrates that our algorithm performs well in predicting video quality and is competitive with current state-of-the-art VQA algorithms.

Video Quality Experts Group: Current results and future directions

Abstract: The Video Quality Experts Group (VQEG) was formed in October 1997 to address video quality issues. The group is composed of experts from various backgrounds and affiliations, including participants from several internationally recognized organizations working int he field of video quality assessment. The first task undertaken by VQEG was to provide a validation of objective video quality measurement methods leading to recommendations in both the telecommunications and radiocommunication sectors of the International Telecommunications Union. To this end, VQEG designed and executed a test program to compare subjective video quality evaluations to the predictions of a number of proposed objective measurement methods for video quality in the bit rate range of 768 kb/s to 50 Mb/s. The results of this test show that there is no objective measurement system that is currently able to replace subjective testing. Depending on the metric used for evaluation, the performance of eight or nine models was found to be statistically equivalent, leading to the conclusion that no single model outperforms the others in all cases. The greatest achievement of this first validation effort is the unique data set assembled to help future development of objective models.

Cross-Layer Packetization and Retransmission Strategies for Delay-Sensitive Wireless Multimedia Transmission

Abstract: Existing wireless networks provide dynamically varying resources with only limited support for the quality of service required by the bandwidth-intense, loss-tolerant and delay-sensitive multimedia applications. This variability of resources does not significantly impact delay insensitive data transmission (e.g., file transfers), but has considerable consequences for multimedia applications. Recently, the research focus has been to adapt existing algorithms and protocols at the lower layers of the protocol stack to better support multimedia transmission applications and conversely, to modify application layer solutions to cope with the varying wireless networks resources. In this paper, we show that significant improvements in wireless multimedia performance can be obtained by deploying a joint application-layer adaptive packetization and prioritized scheduling and MAC-layer retransmission strategy. We deploy a state-of-the-art wavelet coder for the compression of the video data that enables on-the-fly adaptation to changing channel conditions and inherent prioritization of the video bitstream. We pose the cross-layer problem as a distortion minimization given delay constraints and derive analytical solutions by modifying existing joint source-channel coding theory aimed at fulfilling rate, rather than delay, constraints. We also propose real-time algorithms that explicitly consider the available information about previously transmitted packets. The obtained results show significant improvements in terms of video quality as opposed to ad-hoc optimizations currently deployed, while the complexity associated with performing this optimization in real time, i.e., at transmission time, is limited

Rule-based video classification system for basketball video indexing

Abstract: Current information and communication technologies provide the infrastructure to send bits anywhere, but do not presume to handle information at the semantic level. This paper investigates the use of video content analysis and feature extraction and clustering techniques for further video semantic classifications and a supervised rule based video classification system is proposed. This system can be applied to the applications such as on-line video indexing, filtering and video summaries, etc. As an experiment, basketball video structure will be examined and categorized into different classes according to distinct visual and motional characteristics features by rule-based classifier. The semantics classes, the visual/motional feature descriptors and their statistical relationship are then studied in detail and experiment results based on basketball video will be provided and analyzed.