DocumentCode :
50754
Title :
Competitive Live Evaluations of Activity-Recognition Systems
Author :
Gjoreski, Hristijan ; Kozina, Simon ; Gams, Matjaz ; Lustrek, Mitja ; Alvarez-Garcia, Juan Antonio ; Jin-Hyuk Hong ; Ramos, Julian ; Dey, Anind K. ; Bocca, Maurizio ; Patwari, Neal
Author_Institution :
Jozef Stefan Inst., Ljubljana, Slovenia
Volume :
14
Issue :
1
fYear :
2015
fDate :
Jan.-Mar. 2015
Firstpage :
70
Lastpage :
77
Abstract :
Ensuring the validity and usability of activity recognition approaches requires agreement on a set of standard evaluation methods. Due to the diversity of the sensors and other hardware employed, however, designing, implementing, and accepting standard tests is a difficult task. This article presents an initiative to evaluate activity recognition systems: a living-lab evaluation established through the annual Evaluating Ambient Assisted Living Systems through Competitive Benchmarking-Activity Recognition (EvAAL-AR) competition. In the EvAAL-AR, each team brings its own activity-recognition system; all systems are evaluated live on the same activity scenario performed by an actor. The evaluation criteria attempt to capture practical usability: recognition accuracy, user acceptance, recognition delay, installation complexity, and interoperability with ambient assisted living systems. Here, the authors discuss the competition and the competing systems, focusing on the system that achieved the best recognition accuracy, and the system that was evaluated as the best overall. The authors also discuss lessons learned from the competition and ideas for future development of the competition and of the activity recognition field in general.
Keywords :
assisted living; image recognition; EvAAL-AR; activity-recognition systems; annual evaluating ambient assisted living systems; competitive benchmarking-activity recognition competition; competitive live evaluations; evaluation criteria; installation complexity; interoperability; living-lab evaluation; recognition accuracy; recognition delay; sensor diversity; standard evaluation methods; user acceptance; Artificial intelligence; Benchmark testing; Data models; Design methodology; Intelligent systems; Medical services; Senior citizens; Sensors; Wearable computing; AI applications; activity recognition; artificial intelligence; body-area networks; classifier design and evaluation; design methodology; expert systems; healthcare; intelligent systems; pattern recognition; pervasive computing; wearable computers;
fLanguage :
English
Journal_Title :
Pervasive Computing, IEEE
Publisher :
ieee
ISSN :
1536-1268
Type :
jour
DOI :
10.1109/MPRV.2015.3
Filename :
7030218
Link To Document :
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