Adaptive Live Video Streaming by Priority Drop
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Sharp or smooth?: comparing the effects of quantization vs. frame rate for streamed video
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fine-grained scalable streaming from coarse-grained videos
Proceedings of the 18th international workshop on Network and operating systems support for digital audio and video
Subjective impression of variations in layer encoded videos
IWQoS'03 Proceedings of the 11th international conference on Quality of service
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
Quality adaptation in p2p video streaming based on objective qoe metrics
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
Dynamic adaptive streaming over HTTP: from content creation to consumption
Proceedings of the 20th ACM international conference on Multimedia
Improving context interpretation by using fuzzy policies: the case of adaptive video streaming
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Using fuzzy policies to improve context interpretation in adaptive systems
ACM SIGAPP Applied Computing Review
Benchmarking Peer-to-Peer Systems
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Streaming video over the Internet requires mechanisms that limit the streams' bandwidth consumption within its fair share. TCP streaming guarantees this and provides lossless streaming as a side-effect. Adaptation by packet drop does not occur in the network, and excessive startup latency and stalling must be prevented by adapting the bandwidth consumption of the video itself. However, when the adaptation is performed during an ongoing session, it may influence the perceived quality of the entire video and result in improved or reduced visual quality of experience. We have investigated visual artifacts that are caused by adaptive layer switching -- we call them flicker effects -- and present our results for handheld devices in this paper. We considered three types of flicker, namely noise, blur and motion flicker. The perceptual impact of flicker is explored through subjective assessments. We vary both the intensity of quality changes (amplitude) and the number of quality changes per second (frequency). Users' ability to detect and their acceptance of variations in the amplitudes and frequencies of the quality changes are explored across four content types. Our results indicate that multiple factors influence the acceptance of different quality variations. Amplitude plays the dominant role in delivering satisfactory video quality, while frequency can also be adjusted to relieve the annoyance of flicker artifacts.