30,111 research outputs found
Web based lecture technologies: blurring the boundaries between face to face and distance learning
Web based lecture technologies (WBLT) have gained popularity amongst universities in Australia as a tool for delivering lecture recordings to students in close to real time. This paper reports on a selection of results from a larger research project investigating the impact of WBLT on teaching and learning. Results show that while staff see the advantages for external students, they question the extent to which these advantages apply to internal students. In contrast both cohorts of students were positive about the benefits of the technologies for their learning and they adopted similar strategies for their use. With the help of other technologies, some external students and staff even found WBLT useful for fostering communication between internal and external students. As such, while the traditional boundary between internal and external students seems to remain for some staff, students seem to find the boundary much less clear
Objective assessment of region of interest-aware adaptive multimedia streaming quality
Adaptive multimedia streaming relies on controlled
adjustment of content bitrate and consequent video quality variation in order to meet the bandwidth constraints of the communication
link used for content delivery to the end-user. The values of the easy to measure network-related Quality of Service metrics have no direct relationship with the way moving images are
perceived by the human viewer. Consequently variations in the video stream bitrate are not clearly linked to similar variation in the user perceived quality. This is especially true if some human visual system-based adaptation techniques are employed. As research has shown, there are certain image regions in each frame of a video sequence on which the users are more interested than in the others. This paper presents the Region of Interest-based Adaptive Scheme (ROIAS) which adjusts differently the regions within each frame of the streamed multimedia content based on the user interest in them. ROIAS is presented and discussed in terms of the adjustment algorithms employed and their impact on the human perceived video quality. Comparisons with existing approaches, including a constant quality adaptation scheme across the whole frame area, are performed employing two objective metrics which estimate user perceived video quality
QoE-Based Low-Delay Live Streaming Using Throughput Predictions
Recently, HTTP-based adaptive streaming has become the de facto standard for
video streaming over the Internet. It allows clients to dynamically adapt media
characteristics to network conditions in order to ensure a high quality of
experience, that is, minimize playback interruptions, while maximizing video
quality at a reasonable level of quality changes. In the case of live
streaming, this task becomes particularly challenging due to the latency
constraints. The challenge further increases if a client uses a wireless
network, where the throughput is subject to considerable fluctuations.
Consequently, live streams often exhibit latencies of up to 30 seconds. In the
present work, we introduce an adaptation algorithm for HTTP-based live
streaming called LOLYPOP (Low-Latency Prediction-Based Adaptation) that is
designed to operate with a transport latency of few seconds. To reach this
goal, LOLYPOP leverages TCP throughput predictions on multiple time scales,
from 1 to 10 seconds, along with an estimate of the prediction error
distribution. In addition to satisfying the latency constraint, the algorithm
heuristically maximizes the quality of experience by maximizing the average
video quality as a function of the number of skipped segments and quality
transitions. In order to select an efficient prediction method, we studied the
performance of several time series prediction methods in IEEE 802.11 wireless
access networks. We evaluated LOLYPOP under a large set of experimental
conditions limiting the transport latency to 3 seconds, against a
state-of-the-art adaptation algorithm from the literature, called FESTIVE. We
observed that the average video quality is by up to a factor of 3 higher than
with FESTIVE. We also observed that LOLYPOP is able to reach a broader region
in the quality of experience space, and thus it is better adjustable to the
user profile or service provider requirements.Comment: Technical Report TKN-16-001, Telecommunication Networks Group,
Technische Universitaet Berlin. This TR updated TR TKN-15-00
Virtual Reference for Video Collections: System Infrastructure, User Interface and Pilot User Study
A new video-based Virtual Reference (VR) tool called VideoHelp was designed and developed to support video
navigation escorting, a function that enables librarians to co-navigate a digital video with patrons in the web-based
environment. A client/server infrastructure was adopted for the VideoHelp system and timestamps were used to achieve
the video synchronization between the librarians and patrons. A pilot usability study of using VideoHelp prototype in video seeking was conducted and the preliminary results demonstrated that the system is easy to learn and use, and real-time assistance from virtual librarians in video navigation is desirable on a conditional basis
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