No-reference bitstream-based visual quality impairment detection for high definition H.264/AVC encoded video sequences

Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives

No-reference bitstream-based impairment detection for high efficiency video coding

Video distribution over error-prone Internet Protocol (IP) networks results in visual impairments on the received video streams. Objective impairment detection algorithms are crucial for maintaining a high Quality of Experience (QoE) as provided with IPTV distribution. There is a lot of research invested in H.264/AVC impairment detection models and questions rise if these turn obsolete with a transition to the successor of H.264/AVC, called High Efficiency Video Coding (HEVC). In this paper, first we show that impairments on HEVC compressed sequences are more visible compaired to H.264/AVC encoded sequences. We also show that an impairment detection model designed for H.264/AVC could be reused on HEVC, but that caution is advised. A more accurate model taking into account content classification needed slight modification to remain applicable for HEVC compression video content

Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks

Mobile ad hoc networks (MANETs) offer an excellent scenario for deploying communication applications because of the connectivity and versatility of this kind of networks. In contrast, the topology is usually extremely dynamic causing high rate of packet loss, so that ensuring a specific Quality of Service (QoS) for real-time video services becomes a hard challenge. In this paper, we evaluate the effect of using Multiple Description Coding (MDC) and Forward Error Correction (FEC) techniques for improving video quality in a multimedia content distribution system. A hybrid architecture using fixed and wireless ad hoc networks is proposed, which enables the use of multipoint-to-point transmission. MDC and FEC mechanisms can be combined with multipath transmission to increase the network efficiency and recover lost packets, improving the overall Quality of Experience (QoE) of the receiver. Simulations have been analyzed paying attention to objective parameters (Peak Signal to Noise Ratio, Packet Delivery Ratio, Decodable Frame Rate and interruptions) and subjective parameters. Results show that MDC increases the probability of packet delivery and FEC is able to recover lost frames and reduce video interruptions in moderate mobility scenarios, resulting in the improvement of video quality and the final user experience.This work was supported by project MIQUEL (TEC2007- 68119-C02-01/TCM) of the Spanish Ministry of Education and Science. The authors would like to thank the Editor and the reviewers for helpful suggestions to improve the quality of this paper.Acelas Delgado, P.; Arce Vila, P.; Guerri Cebollada, JC.; Castellanos Hernández, WE. (2014). Evaluation of the MDC and FEC over the quality of service and quality of experience for video distribution in ad hoc networks. Multimedia Tools and Applications. 68(3):969-989. https://doi.org/10.1007/s11042-012-1111-3969989683Apostolopoulos JG, Wong T, Tan W, Wee SJ (2002) On multiple description streaming with content delivery networks. IEEE INFOCOMBoukerche A (2009) Algorithms and protocols for wireless and mobile ad hoc networks. John Wiley & Sons IncChow CO, Ishii H (2007) Enhancing real-time video streaming over mobile ad hoc networks using multipoint-to-point communication. Comput Commun 30:1754–1764Clausen T, Jacquet P (2003) Optimized link state routing protocol (OLSR), RFC 3626Corrie B et al (2003) Towards quality of experience in advanced collaborative environments. Third Annual Workshop on Advanced Collaborative EnvironmentsGabrielyan E, Hersch R (2006) Reliable multi-path routing schemes for real-time streaming. International Conference on Digital Telecommunications, pp 65–65Gandikota VR, Tamma BR, Murthy CSR (2008) Adaptive-FEC based packet loss resilience scheme for supporting voice communication over adhoc wireless networks. IEEE Trans Mobile Comput 7:1184–1199Gharavi H (2008) Multi-channel for multihop communication links. International Conference on Telecommunications, pp 1–6Grega M, Janowski L, Leszczuk M, Romaniak P, Papir Z (2008) Quality of experience evaluation for multimedia services. Przegląd Telekomunikacyjny i Wiadomości Telekomunikacyjne 4:142–153Hsieh MY, Huang YM, Chian TC (2007) Transmission of layered video streaming via multi-path on ad hoc networks. Multimed Tool Appl 34:155–177ITU—International Telecommunication Union (2007) Definition of quality of experience (QoE)”, Reference: TD 109rev2 (PLEN/12)ITU-R Recommendation BT.500-12 (2009) Methodology for the subjective assessment of the quality of television pictures. International Telecommunication Union, GenevaITU-T Recommendation P.910 (2000) Subjective video quality assessment methods for multimedia applications. International Telecommunication Union, GenevaKao KL, Ke ChH, Shieh CH (2006) An advanced simulation tool-set for video transmission performance evaluation. IEEE Region 10 Conference, pp 1–40Ke CH et al (2006) A novel realistic simulation tool for video transmission over wireless network. Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trsutworthy ComputingKeisuke U, Cheeonn C, Hiroshi I (2008) A study on video performance of multipoint-to-point video streaming with multiple description coding over ad hoc networks. EEJ Trans Electron, Inf Syst 128:1431–1437Kilkki K (2008) Quality of experience in communications ecosystem. J Univers Comput Sci 14:615–624Li A (2007) RTP payload format for generic forward error correction. RFC 5109, Dec. 2007Li J, Blake C, Couto DD, Lee H, Morris R (2001) Capacity of ad hoc wireless networks. 7th Annual International Conference on Mobile Computing and Networking, pp 16–21Liao Y, Gibson JD (2011) Routing-aware multiple description video coding over mobile ad-hoc networks. IEEE Trans Multimed 13:132–142Lindeberg M, Kristiansen S, Plagemann T, Goebel V (2011) Challenges and techniques for video streaming over mobile ad hoc networks. Multimed Syst 17:51–82Mao S et al (2003) Video transport over ad hoc networks: multistream coding with multipath transport. IEEE J Sel Area Comm 21:1721–1737Ni P (2009) Towards Optimal Quality of Experience Via Scalable Video Coding. Mälardalen University Press Licentiate Theses, SwedenPinson MH, Wolf S (2004) A new standardized method for objectively measuring video quality. IEEE Trans Broadcast 50:312–322Rong B, Qian Y, Lu K, Hu RQ, Kadoch M (2010) Multipath routing over wireless mesh networks for multiple description video transmission. IEEE J Sel Area Comm 28:321–331Schierl T, Ganger K, Hellge C, Wiegand T, Stockhammer T (2006) SVC-based multisource streaming for robust video trans- mission in mobile ad hoc networks. IEEE Wireless Comm 13:96–103Schierl T, Stockhammer T, Wiegand T (2007) Mobile video transmission using scalable video coding. IEEE Trans Circ Syst Video Tech 17:1204–1217Schwarz H, Marpe D, Wiegand T (2007) Overview of the scalable video coding extension of the H.264/AVC standard. IEEE Trans Circ Syst Video Tech 17:1103–1120VQEG (2008) Video quality experts group. Available online: http://www.vqeg.orgWang Z et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13:600–612Wei W, Zakhor A (2004) Robust multipath source routing protocol (RMPSR) for video communication over wireless ad hoc net- works. Proceedings of IEEE International Conference on Multimedia and Expo 2:1379–1382Winkler S, Mohandas P (2008) The evolution of video quality measurement: from PSNR to hybrid metrics. IEEE Trans Broadcast 54:660–668Xunqi Y, Modestino JW, Bajic IV (2005) Performance analysis of the efficacy of packet-level FEC in improving video transport over networks. IEEE International Conference on Image Processing 2:177–180Zink M, Schmitt J, Steinmetz R (2005) Layer-encoded video in scalable adaptive streaming. IEEE Trans Multimed 7:75–8

Constructing a no-reference H.264/AVC bitstream-based video quality metric using genetic programming-based symbolic regression

In order to ensure optimal quality of experience toward end users during video streaming, automatic video quality assessment becomes an important field-of-interest to video service providers. Objective video quality metrics try to estimate perceived quality with high accuracy and in an automated manner. In traditional approaches, these metrics model the complex properties of the human visual system. More recently, however, it has been shown that machine learning approaches can also yield competitive results. In this paper, we present a novel no-reference bitstream-based objective video quality metric that is constructed by genetic programming-based symbolic regression. A key benefit of this approach is that it calculates reliable white-box models that allow us to determine the importance of the parameters. Additionally, these models can provide human insight into the underlying principles of subjective video quality assessment. Numerical results show that perceived quality can be modeled with high accuracy using only parameters extracted from the received video bitstream

Suitability of Transport Techniques for Video Transmission in IP Networks

The paper discusses the problem of video transmission in an IP network. The authors consider the ability of using the most popular video codecs that use both the MPEG2 Transport Stream and Dynamic Adaptive Streaming over Hypertext Transfer Protocol (DASH). The main emphasis was given to ensuring the quality of service and quality assessment methods, taking into account not only the service- or network provider’s point of view but also the end user’s perspective. Two quality assessment approaches were presented, i.e. objective and subjective methods. The authors presented the results of the quality evaluation for H.264/MPEG-4, H.265/HEVC and VP9 codecs. The objective measurements, proved by statistical analysis of user opinion scores, confirmed the ability of using H.265 and VP9 codecs in both real time and streaming transmissions, while the quality of video streaming over HTTP with the H.264 codec proved inadequate. The authors also presented a connection between the dynamics of network bandwidth changing and MPEG-DASH mechanism operation and their influence on thequality experienced by users

QoE for Mobile Streaming

No abstract

Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided