Application of static gesture segmentation based on an improved canny operator

Gong, Shenjian; Li, Guangqiang; Yong-ju, Zhang; Li, Changdi; Yu, Lei

doi:10.1049/joe.2018.9377

Cited by 17 publications

(6 citation statements)

References 19 publications

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“…These steps are performed in the specified order. Recently, some academics have made enhancements to the Canny algorithm, resulting in enhanced accuracy to some degree [56]. However, this paper solely employed edge detection on either two or four inclines of the roof, and the image content was very uncomplicated with limited intricacy.…”

Section: Feature Line Extractionmentioning

confidence: 99%

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Clouds

Zhou,

Fu,

Deng

et al. 2024

Buildings

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Traditional Chinese buildings serve as a carrier for the inheritance of traditional culture and national characteristics. In the context of rural revitalization, achieving the 3D reconstruction of traditional village buildings is a crucial technical approach to promoting rural planning, improving living environments, and establishing digital villages. However, traditional algorithms primarily target urban buildings, exhibiting limited adaptability and less ideal feature extraction performance for traditional residential buildings. As a result, guaranteeing the accuracy and reliability of 3D models for different types of traditional buildings remains challenging. In this paper, taking Jingping Village in Western Hunan as an example, we propose a method that combines multiple algorithms based on the slope segmentation of the roof to extract feature lines. Firstly, the VDVI and CSF algorithms are used to extract the building and roof point clouds based on the MVS point cloud. Secondly, according to roof features, village buildings are classified, and a 3D roof point cloud is projected into 2D regular grid data. Finally, the roof slope is segmented via slope direction, and internal and external feature lines are obtained after refinement through Canny edge detection and Hough straight line detection. The results indicate that the CSF algorithm can effectively extract the roofs of I-shaped, L-shaped, and U-shaped traditional buildings. The accuracy of roof surface segmentation based on slope exceeds 99.6%, which is significantly better than the RANSAC algorithm and the region segmentation algorithm. This method is capable of efficiently extracting the characteristic lines of roofs in low-rise buildings within traditional villages. It provides a reference method for achieving the high-precision modeling of traditional village architecture at a low cost and with high efficiency.

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Section: Feature Line Extractionmentioning

confidence: 99%

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Clouds

Zhou,

Fu,

Deng

et al. 2024

Buildings

View full text Add to dashboard Cite

show abstract

“…Transforming images from the RGB space to the YCrCb space reduces the impact of illumination while remaining convenient and suitable for gesture segmentation. In 2019, Gong et al [5] utilized the YCrCb space along with an adaptive thresholding algorithm and filter enhancements for Canny operators, revealing distinct gesture contours during segmentation. However, this method is limited to single-frame static gesture recognition.…”

Section: Static Gesture Segmentationmentioning

confidence: 99%

Review of vision-based gesture recognition technology

bao,

dai,

2024

International Conference on Optics and Machine Vision (ICOMV 2024)

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With the emergence of deep learning methodologies, vision-based gesture recognition technology has continuously advanced. This paper primarily delves into four main stages of vision-based gesture recognition: gesture segmentation, gesture tracking, feature extraction, and gesture classification. It sequentially introduces pertinent techniques from representative literature spanning from 2018 to 2023. Based on this analysis, the current status of vision-based gesture recognition technology is examined, paving the way for predicting its future trends and developments.

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“…Edge detection based on the Canny operator has five main steps, which are Gaussian smoothing denoising, pixel gradient calculation, non-maximum suppression, double thresholding to determine potential edge points and lagged edge point tracking, in that order. In recent years, some scholars have improved the Canny algorithm in many ways, which has improved the accuracy of Canny to a certain extent [ 30 ] . However, this paper only applies edge detection to two or four slopes of the roof, and the image content is relatively simple without much detail.…”

Section: Feature Line Extractionmentioning

confidence: 99%

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud

Fu,

Deng,

Yan

et al. 2023

Preprint

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The extraction of roof feature lines is an important foundation for realizing large-scale and batch 3D modeling. However, the current traditional point cloud segmentation algorithms do not have satisfactory results in extracting roof feature lines of Chinese traditional residential buildings. In this paper, taking Jingping Village in Western Hunan as an example, we propose a method that combines multiple algorithms based on slope segmentation of roof patches to extract feature lines. Firstly, VDVI and CSF algorithms are used to extract the building and roof point cloud based on the MVS point cloud. Secondly, according to roof features, village buildings are classified, and 3D roof point cloud is projected into 2D regular grid data. Finally, the roof slope is segmented via slope direction, and internal and external feature lines are obtained after refinement through Canny edge detection and Hough straight line detection. Results reveal that this method effectively extracts feature lines of low-building roofs in traditional villages, with slope-based roof surface segmentation accuracy surpassing 99.6%. This method significantly outperforms the RANSAC algorithm and region segmentation algorithm.

show abstract

Application of static gesture segmentation based on an improved canny operator

Cited by 17 publications

References 19 publications

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Clouds

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Clouds

Review of vision-based gesture recognition technology

The Extraction of Roof Feature Lines of Traditional Chinese Village Buildings Based on UAV Dense Matching Point Cloud

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