Video quality

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

Subjective Quality Evaluation via Paired Comparison: Application to Scalable Video Coding

Abstract: Scalable video coding is a powerful solution for content delivery in many interactive multimedia services due to its adaptability to varying terminal and network constraints. In order to successfully exploit such adaptability, it is necessary to understand users' preference among various scalability options and consequently develop an optimal bit rate adaptation strategy. In this paper, we present a study of subjective quality assessment of scalable video coding, which investigates the influence of the combination of scalability options on perceived quality with the goal of providing guidelines for an adaptive strategy that selects the optimal combination for a given bandwidth constraint. In particular, the study is based on paired comparison of stimuli that is suitable for our goal due to its simplicity and easiness. We propose a new method, called Paired Evaluation via Analysis of Reliability (PEAR), which analyzes paired comparison results and produces not only quality scores but also intuitive measures of confidence of the scores for significance analysis. Results and analysis of extensive subjective tests for two different scalable video codecs and high definition contents are described, from which general consistent conclusions are drawn. The video and subjective data used in the paper are publicly available to the research community.

How fast is too fast? evaluating fast forward surrogates for digital video

Abstract: To support effective browsing, interfaces to digital video libraries should include video surrogates (i.e., smaller objects that can stand in for the videos in the collection, analogous to abstracts standing in for documents). The current study investigated four variations (i.e., speeds) of one form of video surrogate: a fast forward created by selecting every Nth frame from the full video. In addition, it tested the validity of six measures of user performance when interacting with video surrogates. Forty-five study participants interacted with all four versions of the fast forward surrogate, and completed all six performance tasks with each. Surrogate speed affected performance on four of the measures: object recognition (graphical), action recognition, linguistic gist comprehension (full text), and visual gist comprehension. Based on these results, we recommend a fast forward default speed of 1:64 of the original video keyframes. In addition, users should control the choice of fast forward speed to adjust for content characteristics and personal preferences.

Modeling of Rate and Perceptual Quality of Compressed Video as Functions of Frame Rate and Quantization Stepsize and Its Applications

Abstract: This paper first investigates the impact of frame rate and quantization on the bit rate and perceptual quality of compressed video. We propose a rate model and a quality model, both in terms of the quantization stepsize and frame rate. Both models are expressed as the product of separate functions of quantization stepsize and frame rate. The proposed models are analytically tractable, each requiring only a few content-dependent parameters. The rate model is validated over videos coded using both scalable and nonscalable encoders, under a variety of encoder settings. The quality model is validated only for a scalable video, although it is expected to be applicable to a single-layer video as well. We further investigate how to predict the model parameters using the content features extracted from original videos. Results show accurate bit rate and quality prediction (average Pearson correlation >;0.99) can be achieved with model parameters predicted using three features. Finally, we apply rate and quality models for rate-constrained scalable bitstream adaptation and frame rate adaptive rate control. Simulations show that our model-based solutions produce better video quality compared with conventional video adaptation and rate control.

Dynamic backlight adaptation for low-power handheld devices

Abstract: Backlight power minimization can effectively extend battery life for mobile handheld devices. This article proposes an adaptive middleware-based approach to optimize backlight power consumption when playing streaming video. The technique simultaneously minimizes the negative impact on perceived video quality.

MSRA-MM 2.0: A Large-Scale Web Multimedia Dataset

Abstract: In this paper, we introduce the second version of Microsoft Research Asia Multimedia (MSRA-MM), a dataset that aims to facilitate research in multimedia information retrieval and related areas. The images and videos in the dataset are collected from a commercial search engine with more than 1000 queries. It contains about 1 million images and 20,000 videos. We also provide the surrounding texts that are obtained from more than 1 million web pages. The images and videos have been comprehensively annotated, including their relevance levels to corresponding queries, semantic concepts of images, and category and quality information of videos. We define six standard tasks on the dataset: (1) image search reranking; (2) image annotation; (3) query-by-example image search; (4) video search reranking; (5) video categorization; and (6) video quality assessment.