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