The engagement of multimedia with society as whole requires research that addresses how multimedia can be used to connect people with multimedia artifacts that meet their needs in a variety of contexts.
Multimedia plays a significant role in engaging the public with art and other forms of cultural expression, as well as a tool that provides rich entertainment experiences to users. A key challenge is therefore to develop techniques that enable effective engagement within these applications. The focus of this area is on the innovative use of digital multimedia technology in arts, entertainment and culture, to support the creation of multimedia content, artistic interactive and multimodal installations, the analysis of media consumption and user experience, or cultural preservation.
We seek full and short papers in a broad range of integrated artistic and scientific statements describing digital systems for arts, entertainment, and culture. Successful papers should achieve a balance between sophisticated technical content and artistic or cultural purpose.
Topics of interest include, but are not limited to:
Models of interactivity specifically addressing arts and entertainment
Active experience of multimedia artistic content by means of socio-mobile multimodal systems
Analysis of spectator experience in interactive systems or digitally-enhanced performances
Virtual and augmented reality artworks, including hybrid physical/digital installations
Dynamic, generative and interactive multimedia artworks
Creativity support tools
Computational aesthetics in multimedia and multimodal systems
Tools for or case studies on cultural preservation or curation
Navigating, indexing, searching and discovering content in large collections of multimedia is a key concern for users and service providers. In spite of great progress in this area, several technical challenges still persist, in particular with respect to performing semantically aware search and recommendations. In the past decade, there has been an explosive growth of multimedia contents on the Web, desktops, and mobile devices. The deluge of multimedia leads to “information overload” and poses new challenges and requirements for effective and efficient access to multimedia content. Multimedia search and recommendation techniques are essential in order to provide information relevant to users’ information needs.
This area calls for contributions on reporting novel problems, solutions, models, and/or theories that tackle the key issues in searching, recommending, and discovering multimedia content, as well as a variety of multimedia applications based on search and recommendation technologies.
Topics of interest include, but are not restricted to:
Large-scale multimedia indexing, ranking, and re-ranking
Novel representation and scalable quantization for efficient multimedia retrieval
Interactive and collaborative multimedia search
Search, ranking and recommendation for social media data
User intent modeling, query suggestion and feedback mechanisms
Multimedia search in specific domains (e.g., scientific, enterprise, social, fashion)
Summarization and organization of multimedia collections
Knowledge discovery from massive multimedia data
Data representations for recommendation tasks
Multimedia-focused recommendation models
Cross-modal recommendations
Personalization in recommendation
New interaction strategies for recommendation
Diversity in search and recommendation
Generalization of recommendations to new users and/or new content (cold start)
As multimedia collections and services grow, the amount of multimedia data approaches a large scale regime. With big data, new challenges and opportunities emerge. For example, rare patterns in data can become more evident, but more efficient processing is required. Over the past few years, tremendous amount of multimedia data is generated everyday with the advancement of digital devices. Meanwhile, machine learning on large scale multimedia data has become a thriving field with a plethora of theories and tools developed.
The goal is to encourage large scale multimedia data to be shared in the community, to engage researchers to work on large scale multimedia problems, to inform researchers about new developments on large scale multimedia problems, and to identify unique challenges and opportunities.
Topics of interest include, but are not restricted to:
Novel big multimedia data in various fields (e.g., finance, content & entertainment, search, healthcare, life sciences, manufacturing, IoT, transportation, and retail)
Novel applications to big multimedia data in various fields (e.g., finance, content & entertainment, search, healthcare, life sciences, manufacturing, IoT, transportation, and retail)
Large Scale perception problems
High efficiency compression, coding and transmission of multimedia big data
Large scale cloud computing
Green computing for multimedia big data
Interaction, access, visualization of large scale multimedia data
This area seeks novel contributions investigating online social interactions around multimedia systems, streams, and collections. Social media (such as Facebook, Twitter, Flickr, YouTube etc.) has substantially and pervasively changed the communication among organizations, communities, and individuals. Sharing of multimedia objects, such as images, videos, music, associated text messages, and recently even digital activity traces such as fitness tracking measurements, constitutes a prime aspect of many online social systems nowadays. This gives us valuable opportunities to understand user-multimedia interaction mechanisms, to predict user behavior, to model the evolution of multimedia content and social graphs, or to design human-centric multimedia applications and services informed by social media, like analysing and predicting related real-world phenomena.
The submissions in this area should look specifically at methods and systems wherein social factors, such as user profiles, user behaviors and activities, and social relations are organically integrated with online multimedia data to understand media content, media use in an online social environment. Or they should leverage the socially created data to solve challenging problems in traditional multimedia computing, enable applications addressing real-world problems (e.g. sales prediction, brand and environmental monitoring) or address new research problems emergent in the online social media scenario.
The proposed contributions are expected to scale up to serve large online user communities. They should exploit massive online collective behavior by looking at e.g., large-group online interactions and group sentiments aggregated across many users in an online community. They should also be able to handle large, heterogeneous and noisy multimedia collections typical for social media environments. Special emphasis is put on multimodal approaches leveraging multiple information sources and modalities to be found in the social media context.
Topics of interest include, but are not restricted to:
Social media data collection, filtering, and indexing
Social media data representation and understanding
User profiling from social media
Personal information disclosure and privacy aspects of social media
Modeling collective behavior in social media
Multimedia propagation in online social environments
Spatial-temporal context analysis in social media
Monitoring, sensing, prediction and forecasting applications with social media
Multimedia-enabled social sharing of information
Detection and analysis of emergent events in social media collections
Verification of social media content
Evaluation of user engagement around shared media
Convergence between Internet of Things, wearables and social media
Systems and analysis of location-based social media
Network theory and algorithms in social multimedia systems
Models for the spatio-temporal characteristics of social media
Models and systems for analyzing large-scale online sentiments
Area: Multimedia Technology for Autonomous Vehicles
As smart vehicles, robots and smart environments evolve, there are new opportunities for providing rich entertainment and engagement to users. These new platforms will probably require different approaches in comparison to traditional devices. Technology enabling multimedia systems and tackling multimedia problems are essential to autonomous vehicles.
This area calls for contributions on reporting novel problems, solutions, models, and/or theories that tackle the key issues in autonomous vehicles area, as well as a variety of multimedia and machine learning applications powering autonomous vehicles technologies.
Topics of interest include, but are not restricted to:
Multimedia based interaction between human and autonomous vehicles
Autonomous navigation and exploration
Sensor-based advanced driver assistance systems
Real-time perception and prediction of traffic scenes
Efficient pedestrian and object detection
Scene classification and environment understanding
Sensor-based underwater and unmanned aerial vehicles
Visual driver monitoring and driver-vehicle interfaces
Performance evaluation of vehicular applications
Deep learning and other machine learning techniques for vehicle technology
Engagement
Program Chair
Google
Engagement
The engagement of multimedia with society as whole requires research that addresses how multimedia can be used to connect people with multimedia artifacts that meet their needs in a variety of contexts.
Areas
Multimedia Art, Entertainment and Culture
Multimedia Search and Recommendation
Big Data
Digital Society
Multimedia Technology for Autonomous Vehicles
publicity chair
Stanford University
Plenary Talk
Stanford University
TPC Members
TBD
Area: Multimedia Art, Entertainment and Culture
Area Chairs
University of Turin
The Pennsylvania State University
Multimedia plays a significant role in engaging the public with art and other forms of cultural expression, as well as a tool that provides rich entertainment experiences to users. A key challenge is therefore to develop techniques that enable effective engagement within these applications. The focus of this area is on the innovative use of digital multimedia technology in arts, entertainment and culture, to support the creation of multimedia content, artistic interactive and multimodal installations, the analysis of media consumption and user experience, or cultural preservation.
We seek full and short papers in a broad range of integrated artistic and scientific statements describing digital systems for arts, entertainment, and culture. Successful papers should achieve a balance between sophisticated technical content and artistic or cultural purpose.
Topics of interest include, but are not limited to:
Area: Multimedia Search and Recommendation
Area Chairs
CustomerserviceAI
Alibaba
IBM Research
Inria Rennes
Facebook
Navigating, indexing, searching and discovering content in large collections of multimedia is a key concern for users and service providers. In spite of great progress in this area, several technical challenges still persist, in particular with respect to performing semantically aware search and recommendations. In the past decade, there has been an explosive growth of multimedia contents on the Web, desktops, and mobile devices. The deluge of multimedia leads to “information overload” and poses new challenges and requirements for effective and efficient access to multimedia content. Multimedia search and recommendation techniques are essential in order to provide information relevant to users’ information needs.
This area calls for contributions on reporting novel problems, solutions, models, and/or theories that tackle the key issues in searching, recommending, and discovering multimedia content, as well as a variety of multimedia applications based on search and recommendation technologies.
Topics of interest include, but are not restricted to:
Area: Big Data
Area Chairs
University of Rochester
Google
IBM
As multimedia collections and services grow, the amount of multimedia data approaches a large scale regime. With big data, new challenges and opportunities emerge. For example, rare patterns in data can become more evident, but more efficient processing is required. Over the past few years, tremendous amount of multimedia data is generated everyday with the advancement of digital devices. Meanwhile, machine learning on large scale multimedia data has become a thriving field with a plethora of theories and tools developed.
The goal is to encourage large scale multimedia data to be shared in the community, to engage researchers to work on large scale multimedia problems, to inform researchers about new developments on large scale multimedia problems, and to identify unique challenges and opportunities.
Topics of interest include, but are not restricted to:
Area: Digital Society
Area Chairs
Microsoft
Stanford University
Tsinghua University
This area seeks novel contributions investigating online social interactions around multimedia systems, streams, and collections. Social media (such as Facebook, Twitter, Flickr, YouTube etc.) has substantially and pervasively changed the communication among organizations, communities, and individuals. Sharing of multimedia objects, such as images, videos, music, associated text messages, and recently even digital activity traces such as fitness tracking measurements, constitutes a prime aspect of many online social systems nowadays. This gives us valuable opportunities to understand user-multimedia interaction mechanisms, to predict user behavior, to model the evolution of multimedia content and social graphs, or to design human-centric multimedia applications and services informed by social media, like analysing and predicting related real-world phenomena.
The submissions in this area should look specifically at methods and systems wherein social factors, such as user profiles, user behaviors and activities, and social relations are organically integrated with online multimedia data to understand media content, media use in an online social environment. Or they should leverage the socially created data to solve challenging problems in traditional multimedia computing, enable applications addressing real-world problems (e.g. sales prediction, brand and environmental monitoring) or address new research problems emergent in the online social media scenario.
The proposed contributions are expected to scale up to serve large online user communities. They should exploit massive online collective behavior by looking at e.g., large-group online interactions and group sentiments aggregated across many users in an online community. They should also be able to handle large, heterogeneous and noisy multimedia collections typical for social media environments. Special emphasis is put on multimodal approaches leveraging multiple information sources and modalities to be found in the social media context.
Topics of interest include, but are not restricted to:
Area: Multimedia Technology for Autonomous Vehicles
Area Chairs
HERE
Baidu IDL
NICTA
As smart vehicles, robots and smart environments evolve, there are new opportunities for providing rich entertainment and engagement to users. These new platforms will probably require different approaches in comparison to traditional devices. Technology enabling multimedia systems and tackling multimedia problems are essential to autonomous vehicles.
This area calls for contributions on reporting novel problems, solutions, models, and/or theories that tackle the key issues in autonomous vehicles area, as well as a variety of multimedia and machine learning applications powering autonomous vehicles technologies.
Topics of interest include, but are not restricted to: