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About

Torsten Edeler is a specialist in 3D time-of-flight (TOF) sensing technology, with a research focus on improving the accuracy, performance, and real-time applicability of depth imaging systems. His work sits at the intersection of machine vision, computer graphics, and robotics — fields increasingly reliant on compact, efficient depth sensors. Edeler's most significant contributions center on algorithmic enhancements to TOF cameras. His development of the pseudo-four-phase-shift algorithm, introduced in 2009 and expanded in a widely cited 2010 publication (25 citations), demonstrated meaningful performance gains over conventional TOF sensing approaches. Building on this, his 2013 paper on modulation methods incorporating noise models to minimize "wiggling error" — a systematic distortion inherent in lock-in TOF cameras — became his most cited work, attracting 27 citations and addressing one of the field's persistent calibration challenges. Beyond algorithmic innovation, Edeler has contributed to practical deployment of TOF systems, exploring real-time image processing pipelines using reconfigurable processor architectures and uncertainty analysis frameworks to better characterize sensor limitations. His body of work collectively advances the reliability and usability of TOF cameras in demanding real-world applications, providing both theoretical grounding and practical tools for researchers and engineers working with next-generation 3D vision systems.