Development of an instrument measuring user satisfaction of the human-computer interface
CHI '88 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Inside the Smart House
A layered interpretation of human interactions captured by ubiquitous sensors
Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences
Memory cues for meeting video retrieval
Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences
Ubiquitous Home: Real-Life Testbed for Home Context-Aware Service
TRIDENTCOM '05 Proceedings of the First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities
Evaluation of video summarization for a large number of cameras in ubiquitous home
Proceedings of the 13th annual ACM international conference on Multimedia
Interactive experience retrieval for a ubiquitous home
Proceedings of the 3rd ACM workshop on Continuous archival and retrival of personal experences
Designing Smart Homes: The Role of Artificial Intelligence (Lecture Notes in Computer Science)
Designing Smart Homes: The Role of Artificial Intelligence (Lecture Notes in Computer Science)
Modeling human behavior from simple sensors in the home
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
IEEE Transactions on Multimedia
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A system for retrieving video sequences created by tracking humans in a smart environment, by using spatial queries, is presented. Sketches made with a pointing device on the floor layout of the environment are used to formqueries corresponding to locomotion patterns. The sketches are analyzed to identify the type of the query. Directional search algorithms based on the minimum distance between points are applied for finding the best matches to the sketch. The results are ranked according to the similarity and presented to the user. The system was developed in two stages. An initial version of the system was implemented and evaluated by conducting a user study. Modifications were made where appropriate, according to the results and the feedback, to make the system more accurate and usable. We present the details of the initial system, the user study and the results, and the modifications thus made. The overall accuracy of retrieval for the initial system was approximately 93%, when tested on a collection of data from a real-life experiment. This is improved to approximately 97% after the modifications. The user interaction strategy and the search algorithms are usable in any environment for automated retrieval of locomotion patterns. The subjects who evaluated the system found it easy to learn and use. Their comments included several prospective applications for the user interaction strategy, providing valuable insight for future directions.