Coot optimization based Enhanced Global Pyramid Network for 3D hand pose estimation
نویسندگان
چکیده
Abstract Due to its importance in various applications that need human-computer interaction (HCI), the field of 3D hand pose estimation (HPE) has recently got a lot attention. The use technological developments, such as deep learning networks accelerated development reliable HPE systems. Therefore, this paper, based on Enhanced Global Pyramid Network (EGPNet) is proposed. Initially, feature extraction done by backbone model DetNetwork with improved EGPNet. EGPNet enhanced Smish activation function. After extraction, performed correction network. Additionally, enhance performance, Coot optimization algorithm used optimize error between estimated and ground truth pose. effectiveness proposed method experimented Bharatanatyam, yoga, Kathakali sign language datasets different terms area under curve, median end-point-error (EPE) mean EPE. also compared existing algorithms.
منابع مشابه
Dense 3D Regression for Hand Pose Estimation
We present a simple and effective method for 3D hand pose estimation from a single depth frame. As opposed to previous state-of-the-art methods based on holistic 3D regression, our method works on dense pixel-wise estimation. This is achieved by careful design choices in pose parameterization, which leverages both 2D and 3D properties of depth map. Specifically, we decompose the pose parameters...
متن کاملHand3D: Hand Pose Estimation using 3D Neural Network
We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image. Different from previous works that mostly run on 2D depth image domain and require intermediate or post process to bring in the supervision from 3D space, we convert the depth map to a 3D volumetric representation, and feed it into a 3D convolutional neural network(CNN) to directly produce t...
متن کاملCascaded Pyramid Network for Multi-Person Pose Estimation
The topic of multi-person pose estimation has been largely improved recently, especially with the development of convolutional neural network. However, there still exist a lot of challenging cases, such as occluded keypoints, invisible keypoints and complex background, which cannot be well addressed. In this paper, we present a novel network structure called Cascaded Pyramid Network (CPN) which...
متن کاملTemplate-based Pose Estimation and Tracking of 3D Hand Motion
The problem of initialising and tracking three dimensional human hand motion from monocular view is addressed in this thesis. We aim to solve the initialisation and tracking in a unified framework. To that end, tracking is formulated as pose estimation of human hand at every frame. The estimated poses at each frame are then combined into smooth trajectories. Template matching forms the basic bu...
متن کامل3D Hand Pose Estimation with Neural Networks
We propose the design of a real-time system to recognize and interpret hand gestures. The acquisition devices are low cost 3D sensors. 3D hand pose will be segmented, characterized and track using growing neural gas (GNG) structure. The capacity of the system to obtain information with a high degree of freedom allows the encoding of many gestures and a very accurate motion capture. The use of h...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Machine learning: science and technology
سال: 2022
ISSN: ['2632-2153']
DOI: https://doi.org/10.1088/2632-2153/ac9fa5