Dear Member of the SIGMM Community, Welcome to the December issue of the SIGMM Records in 2011. We can announce the first call for nominations for ACM SIGMM’s new award, the Nicolas Georganas TOMCCAP Award, which will be awarded for the best paper that was published in ACM TOMCCAP in …
Read more → PhD Thesis Summary
Wireless sensor and actuator networks are comprised of embedded systems with sensing, actuation, computation, and wireless communication capabilities. Their untethered character provides installation flexibility and has in consequence led to their application in a large range of domains, e.g. environmental and habitat monitoring, or industrial process surveillance and control. Besides …
Read more → PhD Thesis Summary
This thesis discusses three major issues that arise in the context of non-sequential usage of multimedia content, i.e. a usage, where users only access content that is interesting for them. These issues are (1) semantically meaningful segmentation of videos, (2) composition of new video streams with content from different sources …
Read more → PhD Thesis Summary
IP-based packet-switched networks have become one of the main content distribution platforms for emerging multimedia services such as IPTV, thanks to the rapidly growing bandwidth and exclusive inter-networking and interactivity features of IP-based networks. Meanwhile, high quality video content services are becoming particularly popular within content delivery networks (CDN). During …
Read more → Award Opportunity
The Editor in Chief of ACM TOMCCAP invites you to nominate candidates for the ACM Transactions on Multimedia Computing, Communications and Applications Nicolas D. Georganas Best Paper.
Award Opportunity
The Association for Computing Machinery, founded in 1947, is the oldest and largest educational and scientific society dedicated to the computing profession, and today has 100,000 members around the world. To encourage historical research, the ACM History Committee plans to make two types of awards.
Free or Open Source Item
At Utrecht University, we have created the Utrecht Multi-Person Motion (UMPM) benchmark to evaluate human motion capturing algorithms for multiple subjects in a similar way as HumanEva does for a single subject. It includes 10 different multi-person scenarios including interaction, each with 1-4 persons. Per scenario, we provide four synchronized …
Read more →