Head Pose Estimation
Head pose estimation (HPE) aims to determine the orientation and position of a person's head in 3D space from images or videos. Current research emphasizes improving accuracy and robustness across a full range of head orientations, particularly addressing challenges like occlusions and variations in lighting and viewpoint, often employing deep learning models such as convolutional neural networks and transformers. These advancements are crucial for applications ranging from human-robot interaction and driver monitoring to medical simulations and personalized learning systems, where accurate understanding of head pose is essential for effective interaction and analysis.
Papers
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