Search results for "Visual comparison"
showing 4 items of 4 documents
Multi-resolution quality-based video coding system for DASH scenarios
2021
Today, more than 85% of Internet traffic has a multimedia component. Video streaming occupies a large part of this percentage mainly because this type of content is provided by the most used applications on the Internet (e.g. Twitch, TikTok, Disney+, YouTube, Netflix, etc.). Most of these platforms use HTTP Adaptive Streaming (HAS) to send this media content to end users in order to ensure a good quality of experience (QoE). But, this QoE should be guaranteed from the video to be transmitted, i.e., the video should have an adequate quality by minimizing the bitrate before transmission. In order to solve this issue, we present a system capable of encoding a video in several resolutions given…
Quantification of DNA and RNA: a Quantitative Visual Comparison
2002
The analytical procedure for the quantification of DNA and RNA described is the quantitative visual comparison of an unknown sample with known standards. This is quick and easy to do, suitable for amounts of sample as small as 10 ng. Keywords: DNA; RNA; rapid quantification
Measuring Perceived Ceiling Height in a Visual Comparison Task
2017
When judging interior space, a dark ceiling is judged to be lower than a light ceiling. The method of metric judgments (e.g., on a centimetre scale) that has typically been used in such tasks may reflect a genuine perceptual effect or it may reflect a cognitively mediated impression. We employed a height-matching method in which perceived ceiling height had to be matched with an adjustable pillar, thus obtaining psychometric functions that allowed for an estimation of the point of subjective equality (PSE) and the difference limen (DL). The height-matching method developed in this paper allows for a direct visual match and does not require metric judgment. It has the added advantage of pro…
Selection of time windows in the horizontal-to-vertical noise spectral ratio by means of cluster analysis
2016
The selection of the elementary analysis windows in continuous noise recordings for optimal estimation of the mean horizontal‐to‐vertical spectral ratio (HVSR) curve is generally performed by visual inspection of HVSR curves considered as functions of time. Starting from full‐length records, HVSR curves are determined in consecutive time windows of appropriate lengths. Time windows with HVSR curves that are anomalous on the basis of a simple visual inspection are generally ignored in the computation of the average HVSR curve. It is often very difficult to optimize the selection of time windows to be used for the calculation of the HVSR curve representative of a site. The use of nonobjective…