Susanne Oehler

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About

Susanne Oehler is a computer vision researcher whose work centers on stereo vision, real-time image processing, and robotic perception systems. Her research has made meaningful contributions to the development of efficient stereo-correspondence algorithms, particularly through parallelization techniques designed to meet the demanding computational requirements of robotic vision applications. Oehler's most recognized work includes the development of a parallel stereo vision algorithm optimized across multiple processor architectures, including x87 and AVX-enabled CPUs, demonstrating her commitment to practical, high-performance implementations. She further advanced this line of research by accelerating dense stereo-matching across both multi-core CPUs and GPUs, significantly improving processing speed for binocular robotic systems — work conducted within the framework of the CloPeMa research project, an initiative focused on robotic cloth perception and manipulation. A notable contribution to the broader research community is her co-creation of Glasgow's Stereo Image Database of Garments, a specialized dataset of 80 stereo-pair color images with disparity maps and mask annotations, enabling 3D garment point cloud rendering. This resource provides a valuable benchmark for researchers working on cloth perception in robotics. With citations across these publications, Oehler's work continues to support advances in robotic vision and real-time stereo processing.