Munich, Germany

Manuel Nickel


Average Co-Inventor Count = 7.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Manuel Nickel: Innovator in 6D Pose and Shape Estimation

Introduction

Manuel Nickel is a prominent inventor based in Munich, Germany. He has made significant contributions to the field of computer vision, particularly in the area of pose and shape estimation. His innovative approach has led to the development of a unique method that enhances the understanding of object positioning and characteristics from 2D images.

Latest Patents

Manuel Nickel holds a patent for a groundbreaking invention titled "6D pose and shape estimation method." This computer-implemented method involves estimating the 6D pose and shape of one or more objects from a 2D image. The process includes detecting 2D regions of interest within the image, cropping corresponding pixel value arrays, coordinate tensors, and feature maps, and inferring various attributes such as rotation, centroid, distance, size, and shape vector for each object. This patent showcases his expertise in merging computer science with practical applications in object recognition.

Career Highlights

Manuel Nickel is currently employed at Toyota Jidosha Kabushiki Kaisha, where he continues to push the boundaries of technology in the automotive industry. His work focuses on integrating advanced computer vision techniques into vehicle systems, enhancing safety and functionality. With a patent portfolio that includes 1 patent, he has established himself as a key player in innovation.

Collaborations

Throughout his career, Manuel has collaborated with talented individuals such as Sven Meier and Norimasa Kobori. These partnerships have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Manuel Nickel's contributions to the field of pose and shape estimation exemplify the impact of innovative thinking in technology. His work not only advances the understanding of object recognition but also enhances practical applications in various industries.

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