Research projects

Rigid 3D Object Detection Object detection and localization is a crucial step for inspection and manipulation tasks in robotic and industrial applications. We present an object detection and localization scheme for 3D objects that combines intensity and depth data. A novel multimodal, scale- and rotation-invariant feature is used to simultaneously describe the object's silhouette and surface appearance. The object's position is determined by matching scene and model features via a Hough-like local voting scheme. The proposed method is quantitatively and qualitatively evaluated on a large number of real sequences, proving that it is generic and highly robust to occlusions and clutter. Comparisons with state of the art methods demonstrate comparable results and higher robustness with respect to occlusions.

Publications

2018
	T. Hodan, F. Michel, E. Brachmann, W. Kehl, A. Buch, D. Kraft, B. Drost, J. Vidal, S. Ihrke, X. Zabulis, C. Sahin, F. Manhardt, F. Tombari, T.K. Kim, J. Matas, C. Rother BOP: Benchmark for 6D Object Pose Estimation European Conference On Computer Vision (ECCV), Munich, Germany, September 2018. (bib)
2015
	B. Drost, S. Ilic Graph-Based Deformable 3D Object Matching German Conference on Pattern Recognition (GCPR), Aachen, Germany, October 2015. (bib)
2013
	B. Drost, S. Ilic A Hierarchical Voxel Hash for Fast 3D Nearest Neighbor Lookup German Conference on Pattern Recognition (GCPR), Saarbruecken, Germany, September 2013. (bib)
2012
	B. Drost, S. Ilic 3D Object Detection and Localization Using Multimodal Point Pair Features Second Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization & Transmission (3DIMPVT), Zurich, Switzerland, October 2012. (bib)
2010
	B. Drost, Markus Ulrich, N. Navab, S. Ilic Model Globally, Match Locally: Efficient and Robust 3D Object Recognition IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, California (USA), June 2010. (bib)

Research

I'm working towards my Ph.D. on the subject of rigid and non-rigid 3D object detection for industrial applications under the supervision of Dr. Slobodan Ilic. My work is funded by MVTec Software GmbH in Munich. My research interests include

• Rigid and non-rigid 3D object detection in point clouds
• Advanced methods for Hough Transform
• Object detection in multimodal data
• Real-Time computer and machine vision algorithms

This video shows an application of our CVPR 2010 approach for rigid 3D object detection. The robot uses a stereo system to acquire a 3D scan of the scene and detects the object of interest within this scene.

http://www.youtube.com/watch?v=mjfAD5YimUw