@phdthesis {schmidt2011,
	title = {Analysis, Modeling and Dynamic Optimization of 3D Time-of-Flight Imaging Systems},
	volume = {Dissertation},
	year = {2011},
	note = {started 01.07.2008},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ. Heidelberg},
	abstract = {(Kurzfassung) Die vorliegende Arbeit befasst sich mit der Optimierung von 3D-Laufzeitkamerasystemen. Diese neuartigen Kameras erfassen Entfernungsbilder, indem sie die beobachtete Szene aktiv beleuchten und die Laufzeit (Time-of-Flight, ToF) des r{\"u}ckgestreuten Lichtes bestimmen. Dabei werden Tiefenbilder aus mehreren Rohbildern konstruiert, wobei typischerweise zwei dieser Bilder simultan mit Hilfe spezieller korrelierender Sensoren aufgenommen werden. Der wissenschaftliche Beitrag dieser Arbeit setzt sich aus vier Entwicklungen zusammen: Pr{\"a}sentiert wird ein physikalisches Sensor-Modell, welches eine Analyse und Optimierung des Prozesses der Rohbildaufnahme erm{\"o}glicht. Hierauf gest{\"u}tzt wird ein auf einer logarithmischen Kennlinie beruhendes ToF Sensor-Design vorgeschlagen. Aufgrund von Asymmetrien der beiden parallelen Auslesestufen des Sensors ist gegenw{\"a}rtig eine mehrfache Akquisition der Rohbilder notwendig. Dies erm{\"o}glicht eine Korrektur systematischer Fehler. Die vorliegende Arbeit pr{\"a}sentiert eine Methode zur dynamischen Kalibrierung und Kompensation dieser Asymmetrien. Sie erlaubt die Erzeugung von zwei Tiefenkarten aus den urspr{\"u}nglichen Rohdaten (eines Tiefenbildes), und bewirkt so eine Verdopplung der Bildwiederholrate. Da mehrere zu unterschiedlichen Zeiten aufgenommene Rohbilder zu einem einzigen Tiefenbild kombiniert werden, treten bei der Abbildung dynamischer Szenerien Bewegungsartefakte auf. Diese Arbeit stellt eine neue, einfache und robuste Methode zur Detektion und Korrektur solcher Artefakte vor. Die in dieser Arbeit pr{\"a}sentierten Algorithmen besitzen eine Berechnungskomplexit{\"a}t, die auch auf Systemen mit limitierten Ressourcen (z.B.~eingebetteten Systemen) eine Ausf{\"u}hrung in Echtzeit erlaubt. Die Algorithmen werden unter Nutzung eines kommerziellen ToF Systems demonstriert. (Abstract) The present thesis is concerned with the optimization of 3D Time-of-Flight (ToF) imaging systems. These novel cameras determine range images by actively illuminating a scene and measuring the time until the backscattered light is detected. Depth maps are constructed from multiple raw images. Usually two of such raw images are acquired simultaneously using special correlating sensors. This thesis covers four main contributions: A physical sensor model is presented which enables the analysis and optimization of the process of raw image acquisition. This model supports the proposal of a new ToF sensor design which employs a logarithmic photo response. Due to asymmetries of the two read-out paths current systems need to acquire the raw images in multiple instances. This allows the correction of systematic errors. The present thesis proposes a method for dynamic calibration and compensation of these asymmetries. It facilitates the computation of two depth maps from a single set of raw images and thus increases the frame rate by a factor of two. Since not all required raw images are captured simultaneously motion artifacts can occur. The present thesis proposes a robust method for detection and correction of such artifacts. All proposed algorithms have a computational complexity which allows real-time execution even on systems with limited resources (e.g.~embedded systems). The algorithms are demonstrated by use of a commercial ToF camera.},
	url = {http://www.ub.uni-heidelberg.de/archiv/12297},
	author = {Schmidt, Mirko}
}
@conference {schmidt2011a,
	title = {High frame rate for 3D time-of-flight cameras by dynamic sensor calibration},
	booktitle = {Proceedings IEEE International Conference on Computational Photography (ICCP)},
	year = {2011},
	pages = {1--8},
	abstract = {3D Time-of-Flight cameras are able to deliver robust depth maps of dynamic scenes. The frame rate, however, is limited because today{\textquoteright}s systems utilizing two-tap sensors need to acquire the required raw images in multiple instances in order to compute one depth map. These multiple raw images allow canceling out systematic errors introduced by asymmetries in the two taps, which otherwise would distort the reconstructed depth map. This work presents a method to implicitly calibrate these asymmetries of multi-tap 3D Time-of-Flight sensors. The calibration data are gathered from arbitrary live acquisitions possibly in real-time. The proposed correction of raw data supersedes the commonly used averaging technique. Thus it is possible to compute multiple depth maps from a single set of raw images. This increases the frame rate by at least a factor of two. The method is verified using real camera data and is evaluated quantitatively.},
	doi = {10.1109/ICCPHOT.2011.5753121},
	author = {Schmidt, Mirko and Klaus Zimmermann and Bernd J{\"a}hne}
}
@conference {maier-hein2011,
	title = {Towards mobile augmented reality for on-patient visualization of medical images},
	booktitle = {Bildverarbeitung f{\"u}r die Medizin (2011)},
	year = {2011},
	pages = {389--393},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Despite considerable technical and algorithmic developments related to the fields of medical image acquisition and processing in the past decade, the devices used for visualization of medical images have undergone rather minor changes. As anatomical information is typically shown on monitors provided by a radiological work station, the physician has to mentally transfer internal structures shown on the screen to the patient. In this work, we present a new approach to on-patient visualization of 3D medical images, which combines the concept of augmented reality (AR) with an intuitive interaction scheme. The method requires mounting a Time-of-Flight (ToF) camera to a portable display (e.g., a tablet PC). During the visualization process, the pose of the camera and thus the viewing direction of the user is continuously determined with a surface matching algorithm. By moving the device along the body of the patient, the physician gets the impression of being able to look directly into the human body. The concept can be used for intervention planning, anatomy teaching and various other applications that require intuitive visualization of 3D data.},
	doi = {10.1007/978-3-642-19335-4_80},
	author = {Lena Maier-Hein and A. M. Franz and M. Fangerau and Schmidt, Mirko and Alexander Seitel and Sven Mersmann and T. Kilgus and A. Groch and K. Yung and Thiago R. dos Santos and Hans-Peter Meinzer},
	editor = {H. Handels and J. Ehrhardt and Hans-Peter Meinzer and T. Tolxdorff and T. M. Deserno}
}
@conference {maier-hein2010a,
	title = {Accounting for an-iso-tro-pic noise in fine registration of time-of-flight range data with high-resolution surface data},
	booktitle = {Medical Image Computing and Computer-Assisted Intervention (MICCAI 2010)},
	volume = {6361},
	year = {2010},
	pages = {251--258},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Time-of-Flight (ToF) sensors have become a considerable alternative to conventional surface acquisition techniques such as laser range scanning and stereo vision. Application of ToF cameras for the purpose of intra-operative registration requires matching of the noisy surfaces generated from ToF range data onto pre-interventionally acquired high-resolution surfaces. The contribution of this paper is two-fold: Firstly, we present a novel method for fine rigid registration of noisy ToF data with high-resolution surface meshes taking into account both, the noise characteristics of ToF cameras and the resolution of the target mesh. Secondly, we introduce an evaluation framework for assessing the performance of ToF registration methods based on physically realistic ToF range data generated from a virtual scence. According to experiments within the presented evaluation framework, the proposed method outperforms the standard ICP algorithm with respect to correspondence search and transformation computation, leading to a decrease in the target registration error (TRE) of more than 70\%.},
	doi = {10.1007/978-3-642-15705-9_31},
	author = {Lena Maier-Hein and Schmidt, Mirko and A. M. Franz and Thiago R. dos Santos and Alexander Seitel and Bernd J{\"a}hne and J. M. Fitzpatrick and Hans-Peter Meinzer}
}
@conference {schmidt2010,
	title = {Exact modelling of time-of-flight cameras for optimal depth maps},
	booktitle = {International Conference on Computational Photography (ICCP) 2010},
	year = {2010},
	note = {Poster},
	author = {Schmidt, Mirko and Michael Erz and Klaus Zimmermann and Bernd J{\"a}hne}
}
@conference {schmidt2009,
	title = {A physical model of Time-of-Flight 3D imaging systems, including suppression of ambient light},
	booktitle = {3rd Workshop on Dynamic 3-D Imaging},
	volume = {5742},
	year = {2009},
	pages = {1--15},
	publisher = {Springer},
	organization = {Springer},
	abstract = {We have developed a physical model of continuous-wave Time-of-Flight cameras, which focuses on a realistic reproduction of the sensor data. The derived simulation gives the ability to simulate data acquired by a ToF system with low computational effort. The model is able to use an arbitrary optical excitation and to simulate the sampling of a target response by a two-tap sensor, which can use any switching function. Nonlinear photo response and pixel saturation, as well as spatial variations from pixel to pixel like photo response non-uniformity (PRNU) and dark signal non-uniformity (DSNU) can be modeled. Also the influence of interfering background light and on-sensor suppression of ambient light can be simulated. The model was verified by analyzing two scenarios: The cameras response to an increasing, homogeneous irradiation as well as the systematic phase deviation caused by higher harmonics of the optical excitation. In both scenarios the model gave a precise reproduction of the observed data.},
	doi = {10.1007/978-3-642-03778-8_1},
	author = {Schmidt, Mirko and Bernd J{\"a}hne},
	editor = {Reinhard Koch and Andreas Kolb}
}
@mastersthesis {schmidt2008b,
	title = {Optische Methoden zur Form- und Positionserkennung von K{\"o}rpern in Werkzeugmaschinen},
	year = {2008},
	school = {Fried-rich-Schil-ler-Uni-ver-si-t{\"a}t Je-na},
	author = {Schmidt, Mirko}
}
