Topic
Dynamic time warping
About: Dynamic time warping is a research topic. Over the lifetime, 6013 publications have been published within this topic receiving 133130 citations.
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13 Sep 2001
TL;DR: An unsupervised algorithm for segmenting categorical time series that exploits two statistical characteristics of meaningful episodes, and segments text into words successfully in three languages.
Abstract: This paper describes an unsupervised algorithm for segmenting categorical time series. The algorithm first collects statistics about the frequency and boundary entropy of ngrams, then passes a window over the series and has two "expert methods" decide where in the window boundaries should be drawn. The algorithm segments text into words successfully in three languages. We claim that the algorithm finds meaningful episodes in categorical time series, because it exploits two statistical characteristics of meaningful episodes.
60 citations
TL;DR: 10 types of gestures and 1350 gesture samples collected from 15 subjects at three different scenes were classified by the dynamic time warping algorithm and the results achieved an average recognition accuracy up to 97.6%.
Abstract: As a promising component for body sensor networks, the wearable sensors for hand gesture recognition have increasingly received great attention in recent years. By interpreting human intentions through hand gestures, the natural human–robot interaction can be realized in the smart home where the youth and the elderly can perform hand gestures to control the household robot or the robotic wheelchair. Here, a wearable wrist-worn camera sensor was shown to recognize hand trajectory gestures. The moving velocity of the user’s hand was deduced from the matched speeded up robust features keypoints of the moving background of the video sequence. Furthermore, the segmentation of continuous gestures was achieved by detecting the predefined gesture starting signal from the hand region of the image, which was segmented by the lazy snapping algorithm. In this paper, 10 types of gestures and 1350 gesture samples collected from 15 subjects at three different scenes were classified by the dynamic time warping algorithm and the results achieved an average recognition accuracy up to 97.6%. Moreover, the practicability of the proposed system was further demonstrated by controlling a cooperative robot to draw letters on paper.
60 citations
TL;DR: A word spotting method based on dynamic time warping (DTW) and an N-best hypothesis overlap measure and a method to detect correction utterances in spontaneously spoken dialog are combined for the purpose.
Abstract: When we communicate with computers through a speech interface, misrecognition is inevitable. Detection of repetition by users is helpful for the system to detect the error and recover. In this paper, we assume that the utterance includes repetitions for correction and propose a method to detect correction utterances in spontaneously spoken dialog. We combined a word spotting method based on dynamic time warping (DTW) and an N-best hypothesis overlap measure for the purpose. We obtained a recall rate of 92.7p and a precision of 89.1p. We next used the detection of correction utterances to improve recognition accuracy. © 2005 Wiley Periodicals, Inc. Syst Comp Jpn, 36(11): 24–33, 2005; Published online in Wiley InterScience (). DOI 10.1002sscj.20341
59 citations
TL;DR: A genetic algorithm coupled with Dynamic Time Warping (DTW) is proposed to solve the issues of misalignment among the reference systems and the lack of synchronization among the devices in a Vicon environment.
Abstract: This paper presents a methodology for a reliable comparison among Inertial Measurement Units or attitude estimation devices in a Vicon environment. The misalignment among the reference systems and the lack of synchronization among the devices are the main problems for the correct performance evaluation using Vicon as reference measurement system. We propose a genetic algorithm coupled with Dynamic Time Warping (DTW) to solve these issues. To validate the efficacy of the methodology, a performance comparison is implemented between the WB-3 ultra-miniaturized Inertial Measurement Unit (IMU), developed by our group, with the commercial IMU InertiaCube3? by InterSense.
59 citations
TL;DR: Experimental results show that the proposed Structured Dynamic Time Warping (SDTW) approach is robust to the diversity of same handwritten letter, and significantly outperforms state-of-the-art approaches.
59 citations