Monocular depth estimation (MDE), which is the task of using a single image to predict scene depths, has gained considerable interest, in large part owing to the popularity of applying deep learning methods to solve “computer vision ...

In this work, we propose to estimate depth maps for images taken from the train driver viewpoint.

This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning & Applications 2020.

This work is a technical introduction to TOF sensors, from architectural and design issues, to selected image processing and computer vision methods.

The 30-volume set, comprising the LNCS books 12346 until 12375, constitutes the refereed proceedings of the 16th European Conference on Computer Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020.

This thesis evaluates and profiles a monocular depth estimation algorithm in which depth maps are generated from a single image using a non-parametric depth transfer approach. 3D depth from images has a wide range of applications in ...

This is an ideal reference for anyone looking for an understanding of the diverse concepts and ideas around this topic and how we can move towards more general techniques than traditional photometric stereo.

This book constitutes the refereed post-conference proceedings of the 5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020, held in Zhuhai, China, in December 2020.

Computer vision has seen incredible growth since the introduction of large datasets, deep neural networks, and modern computing resources.

Depth sensing is critical for many robotic tasks such as localization, mapping and obstacle detection.