Research on hand sketch recognition method based on Sketch-AlexNet

YaQi Wang; Yi Zhang; WenCui Zhao

doi:10.1117/12.2684306

1 August 2023 Research on hand sketch recognition method based on Sketch-AlexNet

YaQi Wang, Yi Zhang, WenCui Zhao

Proceedings Volume 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023); 127543X (2023) https://doi.org/10.1117/12.2684306
Event: 2023 3rd International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 2023, Hangzhou, China

Abstract

With the advancement of artificial intelligence and image processing technology, hand-drawn sketches can be utilized in diverse applications, such as digital creativity, design, and education, among others, highlighting their vast potential in various fields. However, existing challenges in hand-sketch recognition such as low accuracy and efficiency necessitate the development of an improved recognition method. To address these challenges, a sketch recognition method based on Sketch-AlexNet is proposed. Specifically, a larger first layer convolutional kernel is selected to enhance feature extraction ability, while a smaller step size is used to minimize information loss. Moreover, a set of multiplicative convolutional kernels is introduced to replace the original convolutional structure, enabling the network to extract features across shallow to deep hierarchies. The Sketch-AlexNet model is trained on a self-built hand-drawn sketch dataset, yielding a 9.8% accuracy improvement, better recognition results, and corresponding advancements in recognition speed and stability.

Citation Download Citation

YaQi Wang, Yi Zhang, and WenCui Zhao "Research on hand sketch recognition method based on Sketch-AlexNet", Proc. SPIE 12754, Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023), 127543X (1 August 2023); https://doi.org/10.1117/12.2684306

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