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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TL;DR: Assessment of a promising technique for so-called human-congruous trajectory matching, called Dynamic Time Warping, shows that DTW can significantly improve the results from trajectory extraction when compared to traditional techniques.
Abstract: A well-established task in forensic writer identification focuses on the comparison of prototypical character shapes (allographs) present in handwriting. In order for a computer to perform this task convincingly, it should yield results that are plausible and understandable to the human expert. Trajectory matching is a well-known method to compare two allographs. This paper assesses a promising technique for so-called human-congruous trajectory matching, called Dynamic Time Warping (DTW). In the first part of the paper, an experiment is described that shows that DTW yields results that correspond to the expectations of human users. Since DTW requires the dynamics of the handwritten trace, the "online" dynamic allograph trajectories need to be extracted from the "offline" scanned documents. In the second part of the paper, an automatic procedure to perform this task is described. Images were generated from a large online dataset that provides the true trajectories. This allows for a quantitative assessment of the trajectory extraction techniques rather than a qualitative discussion of a small number of examples. Our results show that DTW can significantly improve the results from trajectory extraction when compared to traditional techniques.
48 citations
27 May 2014
TL;DR: This work conducted an American Sign Language (ASL) recognition experiment on Kinect sign data using DTW for sign trajectory similarity and Histogram of Oriented Gradient (HoG) for hand shape representation and proposes a simple RGB-D alignment tool that can help roughly approximate alignment parameters between the color (RGB) and depth frames.
Abstract: Recognizing sign language is a very challenging task in computer vision. One of the more popular approaches, Dynamic Time Warping (DTW), utilizes hand trajectory information to compare a query sign with those in a database of examples. In this work, we conducted an American Sign Language (ASL) recognition experiment on Kinect sign data using DTW for sign trajectory similarity and Histogram of Oriented Gradient (HoG) [5] for hand shape representation. Our results show an improvement over the original work of [14], achieving an 82% accuracy in ranking signs in the 10 matches. In addition to our method that improves sign recognition accuracy, we propose a simple RGB-D alignment tool that can help roughly approximate alignment parameters between the color (RGB) and depth frames.
48 citations
18 Aug 1997
TL;DR: This work focuses on the use of the dynamic time warping (DTW) technique in the signature verification area, where it is a highly appreciated component of speaker specific isolated word recognisers.
Abstract: We focus on the use of the dynamic time warping (DTW) technique in the signature verification area. The DTW algorithm originates from the field of speech recognition, where it is a highly appreciated component of speaker specific isolated word recognisers. A few years ago the DTW algorithm was successfully introduced in the area of online signature verification. The characteristics of speech recognition and signature verification are however rather different. Starting from these dissimilarities, our objective is to extract an alternative DTW approach that is better suited to the signature verification problem.
48 citations
07 Oct 2012
TL;DR: A novel multiple shots re-identification technique is proposed which combines a standard single shot re-Identification, based on offline training to recognize humans from different views, with a Dynamic Time Warping (DTW) distance.
Abstract: This paper presents a new tracking algorithm to solve on-line the 'Tag and Track' problem in a crowded scene with a network of CCTV Pan, Tilt and Zoom (PTZ) cameras. The dataset is very challenging as the non-overlapping cameras exhibit pan tilt and zoom motions, both smoothly and abruptly. Therefore a tracking-by-detection approach is combined with a re-identification method based on appearance features to solve the re-acquisition problem between non overlapping camera views and crowds occlusions. However, conventional re-identification techniques of multi target trackers, which consist of learning an online appearance model to differentiate the target of interest from other people in the scene, are not suitable for this scenario because the tagged pedestrian moves in an environment where pedestrians walking with them are constantly changing. Therefore, a novel multiple shots re-identification technique is proposed which combines a standard single shot re-identification, based on offline training to recognize humans from different views, with a Dynamic Time Warping (DTW) distance.
48 citations
Proceedings Article•
30 Jul 2005TL;DR: A novel online time warping algorithm is presented which has linear time and space costs, and performs incremental alignment of two series as one is received in real time, and is applied to the alignment of audio signals.
Abstract: Dynamic time warping is not suitable for on-line applications because it requires complete knowledge of both series before the alignment of the first elements can be computed. We present a novel online time warping algorithm which has linear time and space costs, and performs incremental alignment of two series as one is received in real time. This algorithm is applied to the alignment of audio signals in order to track musical performances.
48 citations