18566494. POSE ESTIMATION METHOD AND APPARATUS, DEVICE AND MEDIUM simplified abstract (Beijing Zitiao Network Technology Co., Ltd.)
Contents
POSE ESTIMATION METHOD AND APPARATUS, DEVICE AND MEDIUM
Organization Name
Beijing Zitiao Network Technology Co., Ltd.
Inventor(s)
POSE ESTIMATION METHOD AND APPARATUS, DEVICE AND MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18566494 titled 'POSE ESTIMATION METHOD AND APPARATUS, DEVICE AND MEDIUM
The abstract describes a method for pose estimation, involving acquiring frames of continuous reference images before and after a target image, estimating the pose of the target object in each frame, smoothing rotation and translation components, and generating a final pose estimation for the target object in the target image.
- Acquiring continuous reference images before and after a target image
- Estimating the pose of the target object in each frame
- Smoothing rotation and translation components using algorithms
- Generating a final pose estimation for the target object in the target image
Potential Applications: - Robotics - Augmented reality - Virtual reality - Motion capture - Biomechanics research
Problems Solved: - Accurate pose estimation of objects in images - Smoothing out rotation and translation components - Enhancing the quality of pose estimation in target images
Benefits: - Improved accuracy in pose estimation - Enhanced visualization in AR and VR applications - Better tracking of objects in motion capture systems
Commercial Applications: Title: Advanced Pose Estimation Technology for Robotics and AR/VR Applications This technology can be used in industries such as robotics, entertainment, healthcare, and sports for applications like object tracking, gesture recognition, and animation.
Prior Art: Researchers in the field of computer vision and machine learning have developed various pose estimation algorithms using deep learning techniques and sensor fusion methods. It would be beneficial to explore these existing technologies for comparison with the proposed method.
Frequently Updated Research: Researchers are constantly working on improving pose estimation algorithms by incorporating new deep learning architectures, optimizing computational efficiency, and enhancing robustness to varying environmental conditions.
Questions about Pose Estimation Technology: 1. How does this pose estimation method compare to existing algorithms in terms of accuracy and computational efficiency? 2. What are the potential limitations of this method in real-world applications, and how can they be addressed?
Original Abstract Submitted
A pose estimation method is provided. The method includes: according to timing sequence information, acquiring frames of continuous reference images before and after a target image on timing sequence; acquiring a first pose estimation of a target object in each frame of reference image, a second pose estimation of the target object in a target image; according to a rotation smoothing algorithm, processing a rotation pose component of at least one first pose estimation and a rotation pose component of the second pose estimation, to generate a target rotation pose component; according to a translation smoothing algorithm, processing a translation pose component of each first pose estimation and a translation pose component of the second pose estimation, to generate a target translation pose component; generating a third pose estimation of the target object in the target image according to the target rotation pose component and the target translation pose component.
