The 24th Packet Video Workshop (PV 2019) is devoted to presenting technological advancements and innovations in video and multimedia transmission over packet networks. The workshop provides a unique venue for people from the multimedia and networking fields to meet, interact and exchange ideas. Its charter is to promote the research and development in both established and emerging areas of video streaming and multimedia networking. PV 2019 will be held in Amherst, MA, USA on June 21st, 2019 as a single-track event. The workshop will be co-located with ACM MMSys.
PV 2019 seeks submission of original work in all areas of multimedia networking, including cutting-edge research and novel applications. Authors are especially encouraged to submit papers with real-world experimental results and datasets. Topics of interest include (but are not limited to):
- Adaptive media streaming, content storage, and content delivery
- Novel technologies for interactive audiovisual communications
- Next-generation/future video coding, point cloud compression
- Cloud and P2P based multimedia
- Video streaming over software-defined networks
- Multimedia communications over future networks, such as information-centric networks, next-generation 802.11ax networks and 5G wireless
- Coding and streaming of immersive media, including VR, AR, 360° video and multi-sensory systems
- Machine learning in media coding and streaming systems
- Standardization, such as DASH, MMT, CMAF, OMAF, MiAF, WebRTC, HTTP/2, QUIC, MPTCP, MSE, EME, WebXR, Hybrid Media and WAVE
- Emerging applications: social media, game streaming, personal broadcast, healthcare, industry 4.0, multi-camera surveillance, smart transportation, etc.
Prospective authors are recommended to check the call for papers for both NOSSDAV and Packet Video workshops and submit their work based on the respective scopes. The workshop TPC chairs may redirect a submission or an accepted paper to the other workshop as they feel appropriate after notifying the authors.
Special session on Machine Learning for Video Streaming:
Recent advances in machine learning (ML) techniques have found tremendous success in many applications, ranging from speech recognition to natural language processing to computer vision. The powerful toolset of ML can also help solve various optimization-based problems in video streaming. Research challenges include, but are not limited to:
- Learning and prediction of quality-of-experience (QoE) metrics
- Design of intelligent transport protocols that can self-adapt to different devices or deployment environments
- Automation of network policies for QoE optimization
- General applicability of reinforcement learning
Prospective authors are recommended to submit papers on the respective topics above.
Prospective authors are invited to submit an electronic version of full papers, in PDF format, up to six (6) printed pages in length (double column ACM style format) at the workshop Web site. Authors must prepare their papers in a way that preserves the anonymity of the authors. Please do NOT include the author names under the title. The proceedings will be published by ACM Digital Library. Please submit your paper online through:
- Submission deadline:
February 10, 2019February 24, 2019
- Acceptance notification:
March 22, 2019April 1, 2019
- Camera-ready deadline:
April 7, 2019April 19, 2019
- Submission deadline: