Design and implementation of an efficient data collection pipeline for humanoid robot pose estimation

In this dissertation, we present a novel humanoid robot pose dataset and its construction process. Our purpose is to provide a high-quality dataset that enables more studies on humanoid robot pose related tasks. The goal is to design a dataset collection pipeline that can automatically collect, filt...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Luo, Zhiyuan
مؤلفون آخرون: Xie Lihua
التنسيق: Thesis-Master by Coursework
اللغة:English
منشور في: Nanyang Technological University 2024
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/179923
الوسوم: إضافة وسم
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المؤسسة: Nanyang Technological University
اللغة: English
الوصف
الملخص:In this dissertation, we present a novel humanoid robot pose dataset and its construction process. Our purpose is to provide a high-quality dataset that enables more studies on humanoid robot pose related tasks. The goal is to design a dataset collection pipeline that can automatically collect, filter, annotate raw data collected from the internet. We use object detection, pose estimation and many other computer vision algorithms and techniques in the designing process. More than 750 raw images of humanoids were collected from the internet and 150 videos were crawled for all humanoid robot models. Detailed annotations were made on over 1000 images of humanoid robots. A survey was conducted on various humanoid robot models and their structures. Humanoid robot skeleton was constructed by determining the appropriate keypoints and their relation- ships, and a dataset collection pipeline was designed. Our pipeline can be used to collect data more efficiently and reduce time and labor costs.