What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Machine learning
Otmar Hilliges focuses on Artificial intelligence, Computer vision, Computer graphics, Human–computer interaction and Object.
In his works, Otmar Hilliges performs multidisciplinary study on Artificial intelligence and Iterative closest point.
His 3d model research extends to the thematically linked field of Computer vision.
His study in Computer graphics is interdisciplinary in nature, drawing from both Surface reconstruction, Augmented reality, Motion and Virtual image.
He has researched Human–computer interaction in several fields, including Input device, Gesture, Gesture recognition, 3D computer graphics and Mobile device.
His Object research includes elements of Physics engine and Computational science.
His most cited work include:
- KinectFusion: Real-time dense surface mapping and tracking (2794 citations)
- KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera (1650 citations)
- Digits: freehand 3D interactions anywhere using a wrist-worn gloveless sensor (358 citations)
What are the main themes of his work throughout his whole career to date?
Otmar Hilliges mostly deals with Artificial intelligence, Computer vision, Human–computer interaction, Multimedia and Computer graphics.
His research on Artificial intelligence often connects related areas such as Machine learning.
Gaze, Object, Tracking, Image and Monocular are among the areas of Computer vision where Otmar Hilliges concentrates his study.
His studies deal with areas such as Robot, Mobile device, Gesture and Reinforcement learning as well as Human–computer interaction.
His Multimedia research is multidisciplinary, relying on both Interaction technique and Visualization.
Otmar Hilliges interconnects Augmented reality and Input device in the investigation of issues within Computer graphics.
He most often published in these fields:
- Artificial intelligence (54.33%)
- Computer vision (38.94%)
- Human–computer interaction (22.60%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (54.33%)
- Computer vision (38.94%)
- Gaze (8.65%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Computer vision, Gaze, Reinforcement learning and Robot.
The Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition.
His Computer vision course of study focuses on Benchmark and Artificial neural network.
His Gaze study combines topics from a wide range of disciplines, such as Robotics, End-to-end principle, Tracking, Eye tracking and Ground truth.
His work deals with themes such as Control and Motion planning, which intersect with Reinforcement learning.
His Robot study incorporates themes from Haptic technology and Human–computer interaction.
Between 2019 and 2021, his most popular works were:
- Human Body Model Fitting by Learned Gradient Descent. (10 citations)
- ETH-XGaze: A Large Scale Dataset for Gaze Estimation Under Extreme Head Pose and Gaze Variation (8 citations)
- Weakly Supervised 3D Hand Pose Estimation via Biomechanical Constraints. (6 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Machine learning
Otmar Hilliges mainly focuses on Artificial intelligence, Computer vision, Gaze, Pose and Algorithm.
He undertakes multidisciplinary studies into Artificial intelligence and Modular design in his work.
His primary area of study in Computer vision is in the field of Tracking.
His Gaze study integrates concerns from other disciplines, such as Robotics, End-to-end principle, Calibration, Ground truth and Motion capture.
In his research on the topic of Pose, CAD, Orientation, Speech coding and Rendering is strongly related with Object.
His work carried out in the field of Algorithm brings together such families of science as Gradient descent, Human motion and Robustness.
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