Title: Intelligent home interactive gesture recognition method based on multimodal feature fusion and DTW algorithm

Authors: Yan Luo; Zhaosheng Yang

Addresses: Department of Information Engineering, Shijiazhuang College of Applied Technology, Shijiazhuang, Hebei, China ' Department of Information Engineering, Shijiazhuang College of Applied Technology, Shijiazhuang, Hebei, China

Abstract: In order to improve the accuracy of smart home interactive gesture recognition, a smart home interactive gesture recognition method based on multimodal feature fusion and DTW algorithm is proposed. The sampled gesture data are subjected to moving average filtering, and the effective segments are extracted. A CR3D network model is constructed by integrating residual connections into the 3D-CNN framework and multimodal feature fusion is performed on the video frame sequence and the video optical flow frame sequence. Subsequently, the optimal warping path is determined using the DTW algorithm. The Euclidean distance is replaced by the cumulative distance to derive the gesture recognition result. The results show that the error rate is maintained below 0.5%, the coefficient of variation for the same gesture recognised across multiple users is 0 and the minimum recognition rate for multiple gesture categories reaches 96%. These findings indicate that the proposed method achieves high recognition accuracy.

Keywords: smart home; gesture recognition; multimodal feature fusion; CR3D network model; DTW algorithm.

DOI: 10.1504/IJPD.2025.149699

International Journal of Product Development, 2025 Vol.29 No.3/4, pp.415 - 439

Received: 30 Sep 2024
Accepted: 12 Aug 2025
Published online: 10 Nov 2025 *

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