Computer Vision Using Pose Estimation

Pose estimation involves estimating the position and orientation of objects in a 3D space, it has applications areas such as robotics, augmented reality, human-computer interaction. There are several methods for pose estimation, including model-based, feature-based, direct, hybrid, deep learning-based methods. Each method its own strengths weaknesses, choice depends on specific requirements application, object being estimated, available data. Advancements computer vision machine learning have made possible to achieve high accuracy robustness allowing development wide range innovative applications. will continue be an important area research development, we can expect see further improvements future.