The second edition of the Human-Centered Computational Sensing (HCCS’20) Workshop at PerCom 2020 aims to advance and promote research about how unobtrusive observation of human beings’ cognitive, behavioral, physiological, and contextual data is increasingly enabling new computing experiences. The workshop will additionally stimulate dialog about the implications of computational sensing for society. Traditionally, sensors have been understood narrowly as physiological measurements often captured with wearable devices. This workshop adopts a broader, human-focused view, envisioning sensing as time-evolving measurable data directly linked to individuals and, by extension, to their communities. With this understanding, sensing involves human reactions and interactions observed in spoken, written, or signed language, eye gaze, facial and bodily expressions, social networks, geospatial patterns, and other such human-generated data. Advances in multimodal human data acquisition and fusion have the potential to significantly impact all areas of human life – productivity, health and well-being, training and education, human-computer interaction, accessibility, safety and security, as well as gaming, sports, and entertainment.
Topics of interest
Topics include but are not limited to:
- Novel methodologies for collecting and processing multimodal human sensing data
- Co-sensing of multiple individuals, groups, or communities
- Detection and analysis of human social interactions
- Tracking and localization from human sensing data
- New interventions acting on human-centered computational sensing
- Fusion of multifaceted, heterogeneous, and/or incommensurable human sensing data
- Artificial intelligence and machine learning algorithms for behavioral analysis from human sensing data
- Performance efficiency across hardware and cloud contexts
- Applications of human-centered computational sensing
- Innovative visualizations and representations of human sensing data
- Evaluation metrics and methodologies
- Experimental analysis with human sensing data from real-world applications
- Privacy and ethical considerations for human-centered computational sensing
- Workshop paper submissions: November 11, 2019, 23:59 EST (Extended to December 2, 2019, 23:59 EST)
- Paper notifications: December 20, 2019
- Camera ready submissions: January 31, 2020
- HCCS Workshop at PerCom 2020: March 23, 2020
Submission and Registration:
Authors are invited to submit technical or theoretical papers for presentation at the workshop, describing original, previously unpublished work, which is not currently under review by another workshop, conference, or journal. Papers should present novel perspectives within the general scope of the workshop.
Accepted workshop papers will be included and indexed in the IEEE digital libraries (Xplore).
Papers may be no more than 6 pages in length. Authors can purchase one additional page for the camera ready version. Papers in excess of the page limits will not be considered for review or publication. All papers must be typeset in double-column IEEE format using 10pt fonts on US letter paper, with all fonts embedded. The IEEE LaTeX and Microsoft Word templates, as well as related information, can be found at the IEEE website.
Submission must be made via EDAS using https://edas.info/N26544
It is a requirement that all the authors listed in the submitted paper are also listed in EDAS. The author section of EDAS will be locked after the workshop submission deadline to ensure that conflict-of-interest can be properly enforced during review. If the list of authors differs between the paper and EDAS, the paper may not be reviewed.
Each accepted workshop paper requires a full PerCom registration (no registration is available for workshops only). Papers that are not presented at the workshop will not be published in the proceedings.
- Reynold Bailey, Rochester Institute of Technology, USA
- Michele Girolami, National Research Council of Italy, Italy
- Franca Delmastro, National Research Council of Italy, Italy
- Cecilia Ovesdotter Alm, Rochester Institute of Technology, USA
- Fabio Mavilia, National Research Council of Italy, Italy