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Dynamic time warping (DTW) measures similarity between two data sequences by minimizing an accumulated distance between two sequence samples at each iteration and a cost is computed to assess the level of the similarity. The DTW cost may then be used to assign a sequence to a class if the problem is a classification problem. In machine learning, classification problems are solved using features with...
Gesture recognition is a technology often used in human-computer interaction applications. Dynamic time warping (DTW) is one of the techniques used in gesture recognition to find an optimal alignment between two sequences. Oftentimes a pre-processing of sequences is required to remove variations due to different camera or body orientations or due to different skeleton sizes between the reference gesture...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.