Semantic Space: An Infrastructure for Smart Spaces
IEEE Pervasive Computing
Resolving uncertainty in context integration and abstraction: context integration and abstraction
Proceedings of the 5th international conference on Pervasive services
Extracting tennis statistics from wireless sensing environments
Proceedings of the Sixth International Workshop on Data Management for Sensor Networks
Sports wizard: sports video browsing based on semantic concepts and game structure
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Tennissense: a platform for extracting semantic information from multi-camera tennis data
DSP'09 Proceedings of the 16th international conference on Digital Signal Processing
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Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research, we employ a ubiquitous sensor network to track the movement of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the effort of coaches and players who are required to study matches afterwards. The sensor network is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach.