PosePrior

准确的3D人体姿势先验建模是计算机视觉研究中许多问题的基础。但是，以前的大多数研究要么没有足够多样的人类姿势，要么没有足够的约束来过滤无效姿势。于是PosePrior数据集应运而生，弥补了以前这些数据集的不足。该数据集由几个运动员的各种伸展姿势组成，研究人员可以使用它们来研究与姿势相关的关节角度限制。Accurate 3D human pose prior modeling underpins numerous problems in computer vision research. However, most prior studies either lacked sufficiently diverse human poses or did not have adequate constraints to filter invalid poses. Thus, the PosePrior dataset was developed to address these shortcomings of previous datasets. This dataset consists of various stretching poses of several athletes, which researchers can use to investigate pose-related joint angle constraints.

搜集汇总

背景与挑战

背景概述

PosePrior是一个公开的3D人体姿势先验数据集，旨在弥补以往数据集在姿势多样性和约束方面的不足。它包含多种运动员的伸展姿势，用于支持关节角度限制的相关研究，由马克斯普朗克智能系统研究所于2015年发布。