Object detection and recognition is a topic of significant interest in computer and robot vision. It is required in most applications of computational vision, for example, biometric systems, medical imaging, intelligent cars, factory automation, and image databases.

One of the major challenges in designing object recognition systems is to construct methods that are fast and capable of operating on standard computer platforms. The more developed such systems become, the more urgent becomes the need for a pre-selection system that enables subsequent processing to focus only on relevant data. One mechanism to achieve this is visual attention: it selects regions in a visual scene that are most likely to contain objects of interest. The field of visual attention is currently the focus of much research for both biological and artificial systems.

This monograph presents a complete computational system for visual attention and object detection: VOCUS (Visual Object detection with a CompUtational attention System) is a system capable of automatically selecting regions of interest in images and detecting specific objects. It represents a major step forward on integrating data-driven and model-driven information into a single framework. Additionally, the volume contains an extensive review of the literature on visual attention, detailed evaluations of VOCUS in different settings, and applications of the system in the context of object recognition and robotics.

This book constitutes the refereed proceedings of the 44th DAGM German Conference on Pattern Recognition, DAGM GCPR 2022, which was held during September 27 - 30, 2022.The 37 papers presented in this volume were carefully reviewed and selected from 78 submissions. They were organized in topical sections as follows: machine learning methods; unsupervised, semi-supervised and transfer learning; interpretable machine learning; low-level vision and computational photography; motion, pose estimation and tracking; 3D vision and stereo; detection and recognition; language and vision; scene understanding; photogrammetry and remote sensing; pattern recognition in the life and natural sciences; systems and applications.

This book constitutes the proceedings of the 41st DAGM German Conference on Pattern Recognition, DAGM GCPR 2019, held in Dortmund, Germany, in September 2019. The 43 revised full papers presented were carefully reviewed and selected from 91 submissions. The German Conference on Pattern Recognition is the annual symposium of the German Association for Pattern Recognition (DAGM). It is the national venue for recent advances in image processing, pattern recognition, and computer vision and it follows the long tradition of the DAGM conference series.