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基于双目视觉的电动轮椅行人识别与跟随方法

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为了增强电动轮椅的 自主能力,提出了一种基于双目视觉的电动轮椅行人识别与跟随方法.首先介绍了智能轮椅系统的结构;其次采用基于深度神经网络的行人骨骼关键点检测方法,通过部署行人属性识别模型实现对跟踪目标的重识别并获取位置;最后结合双目视觉实现对行人在相机坐标系下的局部状态跟踪,让轮椅在复杂多变的场景中完成行人跟随任务.实验结果表明,该方法能够有效地识别和跟随行人,并且在不同环境下具有较好的鲁棒性和实用性,为电动轮椅智能化提供了一种有效的解决方案.
Electric Wheelchair Pedestrian Recognition and Following Technology Based on Binocular Vision
A method for electric wheelchair pedestrian recognition and following based on binocular vision is proposed to enhance the autonomy of electric wheelchairs in this paper.Firstly,the intelligent wheelchair system structure of this study is introduced.Secondly,a pedestrian skeleton key point detection method based on deep neural network is adopted,and the tracking target is re-recognized and the position is obtained by deploying a pedestrian attribute recognition model.Finally,combined with binocular vision,the local state tracking of pedestrians in the camera coordinate system is realized,allowing the wheelchair to complete the pedestrian following task in complex and changeable scenes.

intelligent wheelchairdeep learningbinocular visionpedestrian attribute recognitionperson following

聂洪君、赵华杰、裴存存

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扬州大学电气与能源动力工程学院,江苏扬州 225127

智能轮椅 深度学习 双目视觉 行人属性识别 行人跟随

2024

工业控制计算机
中国计算机学会工业控制计算机专业委员会 江苏省计算技术研究所有限责任公司

工业控制计算机

影响因子:0.258
ISSN:1001-182X
年,卷(期):2024.37(2)
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