17 citations · 29 across the 6 of their papers we have counts for
8 papers
BlendTorch: A Real-Time, Adaptive Domain Randomization Library
Christoph Heindl, Lukas Brunner, Sebastian Zambal +1
Solving complex computer vision tasks by deep learning techniques relies on large amounts of (supervised) image data, typically unavailable in industrial environments. The lack of…
Enhanced Human-Machine Interaction by Combining Proximity Sensing with Global Perception
Christoph Heindl, Markus Ikeda, Gernot Stübl +2
The raise of collaborative robotics has led to wide range of sensor technologies to detect human-machine interactions: at short distances, proximity sensors detect nontactile gestu…
End-to-End Defect Detection in Automated Fiber Placement Based on Artificially Generated Data
Sebastian Zambal, Christoph Heindl, Christian Eitzinger +1
Automated fiber placement (AFP) is an advanced manufacturing technology that increases the rate of production of composite materials. At the same time, the need for adaptable and f…
Metric Pose Estimation for Human-Machine Interaction Using Monocular Vision
Christoph Heindl, Markus Ikeda, Gernot Stübl +2
The rapid growth of collaborative robotics in production requires new automation technologies that take human and machine equally into account. In this work, we describe a monocula…
Learning to Predict Robot Keypoints Using Artificially Generated Images
Christoph Heindl, Sebastian Zambal, Josef Scharinger
This work considers robot keypoint estimation on color images as a supervised machine learning task. We propose the use of probabilistically created renderings to overcome the lack…
Spatio-thermal depth correction of RGB-D sensors based on Gaussian Processes in real-time
Christoph Heindl, Thomas Pönitz, Gernot Stübl +2
Commodity RGB-D sensors capture color images along with dense pixel-wise depth information in real-time. Typical RGB-D sensors are provided with a factory calibration and exhibit e…