3D Human Pose Estimation Via Deep Learning Methods
Kamrun Nahar, Huang Xu, Md Helal Hossen, Md Suhel Rana, Md Humayun Kabir, Md Jahidul Islam · Zenodo (CERN European Organization for Nuclear Research) · 2023
This paper presents a novel method for estimating the human body in 3D using depth sensor data. The proposed method utilizes a deep neural network to predict the body joints and a kinematic model to estimate the body shape. The approach utilizes a combination of convolutional and recurrent neural networks, trained on a dataset of human subjects, to accurately predict the positions of key body joints. These joints are then used as input to a kinematic model, which estimates the body shape and pose. The method was estimated on a dataset of human subjects, and the results show that it achieves high delicacy in body joint and shape estimation. The proposed approach outperforms being methods in terms of both delicacy and robustness, and it's suitable to handle a wide range of body acts and movements. also, the system is computationally effective and can run in real- time, making it suitable for a variety of operations similar as virtual reality, mortal- computer commerce, and stir analysis. The capability to directly estimate the human body in 3D is pivotal for a wide range of operations, and this work makes significant benefactions towards this thing. The proposed system is the first to demonstrate that it's possible to directly estimate the body shape and disguise using only depth sensor data, and it opens up new possibilities for a wide range of exploration and operations. In summary, this paper presents a real- time, robust and accurate system for 3D mortal body estimation using depth detector data, which is grounded on a deep neural network armature and kinematic model. The proposed system was estimated on a dataset of human subjects and achieved high delicacy in body joint and shape estimation, outperforming being methods in terms of both delicacy and robustness. And the approach can be used for a variety of operations similar as virtual reality, human- computer interaction, and motion analysis.