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MEDIAPIPE hands tracking

时间:2025-03-07 17:05:48  来源:互联网  作者:
MediaPipe Hands: On-device Real-time Hand Tracking 论文 2021年11月10日 · 在本文中,我们提出了MediaPipe Hands,这是一种端到端的手跟踪解决方案,可在多个平台上实现实时性能。 我们的流水线模型可以在无需任何专用硬件情况下预 更多内容请查看https://zhuanlan.zhihu.com/p/431523776

chuoling.github.ioHands MediaPipe Hands is a high-fidelity hand and finger tracking solution. It employs machine learning (ML) to infer 21 3D landmarks of a hand from just a single frame.更多内容请查看https://chuoling.github.io/mediapipe/solutions/hands.html

GitHubMediaPipe Hands is a high-fidelity hand and finger tracking solution. It employs machine learning (ML) to infer 21 3D landmarks of a hand from just a single frame.更多内容请查看https://github.com/google-ai-edge/mediapipe/blob/master/docs/solutions/hands.md

arXiv.org[2006.10214] MediaPipe Hands: On-device Real-time Hand Tracking 2020年6月18日 · We present a real-time on-device hand tracking pipeline that predicts hand skeleton from single RGB camera for AR/VR applications. The pipeline consists of two models: 作者: Fan Zhang, Valentin Bazarevsky, Andrey Vakunov, Andrei Tkachenka, George Sung, Chuo-Ling Chang, MattCite as: arXiv:2006.10214 [cs.CV]Publish Year: 2020更多内容请查看https://arxiv.org/abs/2006.10214

[论文评析]MediaPipe Hands: On-device Real-time 2022年11月25日 · MediaPipe Hands: On-device Real-time Hand Tracking (From Google) 贡献点或者创新点 提出了实时运行在设备上的多手跟踪,并且只需要一个RGB摄像头就可以。 推理管道由两部分组成:手掌检测器和预测手关节坐 更多内容请查看https://blog.csdn.net/QKK612501/article/details/128041844

https://blog.csdn.net/weixin_43229348/article/details/MediaPipe基础(4)Hands(手) MediaPipe Hands 是一种高保真手和手指跟踪解决方案。它采用机器学习 (ML) 从单个帧中推断出手的 21 个 3D 地标。当前最先进的方法主要依赖于强大的桌面环_mediapipe handszynhx.cn更多内容请查看https://blog.csdn.net/weixin_43229348/article/details/120530937

https://blog.csdn.net/haiyangyunbao813/article/details/windows 基于 MediaPipe 实现 HandTracking_mediapipe hand 2022年1月13日 · MediaPipe Hands 是一种高保真手和手指跟踪解决方案。 它使用 机器学习 (ML) 从单帧中推断出一只手的 21 个 3D 地标。 尽管当前最先进的方法主要依赖于强大的桌面环境 更多内容请查看https://blog.csdn.net/haiyangyunbao813/article/details/122464972

Google Researchhttps://research.google/blog/on-device-real-timeOn-Device, Real-Time Hand Tracking with 2019年8月19日 · 3D hand perception in real-time on a mobile phone via MediaPipe. Our solution uses machine learning to compute 21 3D keypoints of a hand from a video frame. Depth is indicated in grayscale. Our hand tracking 更多内容请查看https://research.google/blog/on-device-real-time-hand-tracking-with-mediapipe/

Google ResearchMediaPipe Hands: On-device Real-time Hand TrackingWe present a real-time on-device hand tracking pipeline that predicts hand skeleton from only single camera input for AR/VR applications. The pipeline consists of two models: 1) a palm 更多内容请查看https://research.google/pubs/mediapipe-hands-on-device-real-time-hand-tracking/

CSDN文库mediapipe手势识别算法图解 其中,MediaPipe Hands是一个基于OpenCV的手势识别解决方案,可以检测到双手并提取手部关节点的坐标信息。 该手势识别模型使用了两个机器学习工作流程:手掌检测器和手部 更多内容请查看https://wenku.csdn.net/answer/2fr8p2o44n

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