Comparison of exact static and dynamic Bayesian context inference methods for activity recognition

2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops, PERCOM Workshops 2010

Volumn , Issue , 2010, Pages 189-195

  Frank, Korbinian ^a,c   Röckl, Matthias ^a   Vera Nadalest, María Iosefa ^b   Robertson, Patrick ^a   Pfeifer, Tom ^c  

^a GERMAN AEROSPACE CENTER DLR   (Germany)

^b UNIVERSITY OF MÁLAGA   (Spain)

^c Ireland   (Ireland)

Author keywords

Acceleration sensors; Activity estimation; Activity recognition; Context inference; Probabilistic inference

Indexed keywords

ACCELERATION DATA; ACCELERATION SENSORS; ACTIVITY RECOGNITION; BAYESIAN; CONTEXT INFERENCE; DATA SETS; DYNAMIC BAYESIAN NETWORK; DYNAMIC NETWORK; INERTIAL MEASUREMENT UNIT; PERFORMANCE INDICATORS; PROBABILISTIC INFERENCE; PROCESSING TIME; STATIC AND DYNAMIC;

BENCHMARKING; DISTRIBUTED PARAMETER NETWORKS; ELECTRIC LOAD SHEDDING; INFERENCE ENGINES; INTELLIGENT NETWORKS; SENSORS; SERVICE ORIENTED ARCHITECTURE (SOA); UNITS OF MEASUREMENT;

BAYESIAN NETWORKS;

EID: 77954023542     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/PERCOMW.2010.5470671     Document Type: Conference Paper

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