2005 · 56 citations · 20 references
ComputingComputer ScienceComputer VisionHuman-computer InteractionSensor FusionAction RecognitionDynamic Time WarpingMobile Human-computer InteractionMobile SensingMultimodal InteractionMultisensor Data IntegrationAccelerometer SensorsBenchmark Dataset DesignBenchmark Dataset DevelopmentBenchmark Dataset EvaluationBenchmark DatasetsHand GesturesMultimodal Context RecognitionMultisensor Fusion
In this paper we present our system for online context recognition of multimodal sequences acquired from multiple sensors. The system uses Dynamic Time Warping (DTW) to recognize multimodal sequences of different lengths, embedded in continuous data streams. We evaluate the performance of our system on two real world datasets: 1) accelerometer data acquired from performing two hand gestures and 2) NOKIA's benchmark dataset for context recognition. The results from both datasets demonstrate that the system can perform online context recognition efficiently and achieve high recognition accuracy.
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Three Myths about Dynamic Time Warping Data Mining
Chotirat Ann Ratanamahatana, Eamonn Keogh · 2005 · 396 citations