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A growing number of modern applications such as position determination, object recognition and collision prevention depend on accurate scene analysis. The estimation of an object's distance relative to an observers position by image analysis or laser scan techniques is thereby still the most time-consuming and expansive part. A lower-priced and much faster alternative is the distance measurement with modulated, coherent infrared light based on the Photo Mixing Detector (PMD) technique. As this approach is a rather new and unexplored method, proper calibration techniques have not been widely investigated yet. This paper describes an accurate distance calibration approach for PMD-based distance sensoring.

A growing number of modern applications such as position determination, online object recognition and collision prevention depend on accurate scene analysis. A low-cost and fast alternative to standard techniques like laser scanners or stereo vision is the distance measurement with modulated, incoherent infrared light based on the Photo Mixing Device (PMD) technique.This paper describes an enhanced calibration approach for PMD-based distance sensors, for which highly accurate calibration techniques have not been widely investigated yet. Compared to other known methods, our approach incorporates additional deviation errors related with the variation of the active illumination incident to the sensor pixels. The resulting calibration yields significantly more precise distance information. Furthermore, we present a simple to use, vision-based approach for the acquisition of the reference data required by any distance calibration scheme, yielding a light-weighted, on-site calibration system with little expenditure in terms of equipment.

Abstract-An important field of reasearch in computer vision is the 3D analysis and reconstruction of objects and scenes for e. g. position determination, online object recognition or collision prevention. Known techniques thereby mainly rely on measuring devices such as laser scanners, stereo camera systems, or comparable algorithms like structure from motion.The rather new Photonic Mixing Device (PMD) technique is based on the time-of-flight principle and measures full-range distance information in real-time. Unfortunately, PMD-based devices have still limited resolution (e. g. 160 × 120 px) and provide only graylevel information. This paper describes a fast algorithmic approach to combine high resolution RGB images with low resolution PMD distance data, acquired using a binocular camera setup. The approach relies completely on fast parallel Graphics Processing Units (GPUs) ressources. Additionally, we introduce a simple but efficient method to detect insufficient color assignments, which are due to the binocular setup.The resulting combined RGBZ-data not only enhances the visual result, but also represents a basis for advanced data processing in e. g. object recognition.

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