Inicio · Capítulos · 14. Señales para visión artificial
14.1.21 Referencias
- [P41-R1] Bazarevsky, Grishchenko et al..
BlazePose: On-device Real-time Body Pose Tracking.
https://arxiv.org/abs/2006.10204
- [P41-R2] Google AI for Developers. MediaPipe
PoseLandmark — 33 pose landmarks.
https://ai.google.dev/edge/api/mediapipe/python/mp/tasks/vision/PoseLandmark
- [P41-R3] Zhang, Bazarevsky et al.. MediaPipe
Hands: On-device Real-time Hand Tracking.
https://arxiv.org/abs/2006.10214
- [P41-R4] Grishchenko, Bazarevsky et al..
BlazePose GHUM Holistic: Real-time 3D Human Landmarks and Pose
Estimation. https://arxiv.org/abs/2206.11678
- [P41-R5] OpenCV. Perspective-n-Point pose
computation and camera-coordinate convention.
https://docs.opencv.org/master/d5/d1f/calib3d_solvePnP.html
- [P41-R6] Luxonis. DepthAI Coordinate
Systems.
https://docs.luxonis.com/software-v3/depthai/depthai-components/coordinate-systems
- [P41-R7] Yan et al.. CIMI4D: A Large Multimodal
Climbing Motion Dataset Under Human-Scene Interactions.
https://openaccess.thecvf.com/content/CVPR2023/html/Yan_CIMI4D_A_Large_Multimodal_Climbing_Motion_Dataset_Under_Human-Scene_Interactions_CVPR_2023_paper.html
- [P41-R8] Yan et al.. ClimbingCap: Multi-Modal
Dataset and Method for Rock Climbing in World Coordinate.
https://openaccess.thecvf.com/content/CVPR2025/html/Yan_ClimbingCap_Multi-Modal_Dataset_and_Method_for_Rock_Climbing_in_World_CVPR_2025_paper.html
- [P41-R9] Maschek and Schedl. The Way Up: A
Dataset for Hold Usage Detection in Sport Climbing.
https://openaccess.thecvf.com/content/CVPR2025W/CVSPORTS/html/Maschek_The_Way_Up_A_Dataset_for_Hold_Usage_Detection_in_CVPRW_2025_paper.html
- [P41-R10] Cao, Simon, Wei and Sheikh. Realtime
Multi-Person 2D Pose Estimation Using Part Affinity Fields.
https://openaccess.thecvf.com/content_cvpr_2017/html/Cao_Realtime_Multi-Person_2D_CVPR_2017_paper.html
- [P41-R11] Güler, Neverova and Kokkinos.
DensePose: Dense Human Pose Estimation in the Wild.
https://openaccess.thecvf.com/content_cvpr_2018/html/Guler_DensePose_Dense_Human_CVPR_2018_paper.html
- [P41-R12] Loper, Mahmood, Romero, Pons-Moll and
Black. SMPL: A Skinned Multi-Person Linear Model.
https://smpl.is.tue.mpg.de/
- [P41-R13] COCO Consortium. COCO Dataset —
person keypoints and evaluation context.
https://cocodataset.org/