Active Vision For Scene Understanding
Download Active Vision For Scene Understanding PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Active Vision For Scene Understanding book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Active Vision for Scene Understanding
Author: Grotz, Markus
language: en
Publisher: KIT Scientific Publishing
Release Date: 2021-12-21
Visual perception is one of the most important sources of information for both humans and robots. A particular challenge is the acquisition and interpretation of complex unstructured scenes. This work contributes to active vision for humanoid robots. A semantic model of the scene is created, which is extended by successively changing the robot's view in order to explore interaction possibilities of the scene.
Multimodal Scene Understanding
Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. - Contains state-of-the-art developments on multi-modal computing - Shines a focus on algorithms and applications - Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning
Intelligent active vision systems for robots
Author: Erik Valdemar Cuevas Jiménez
language: en
Publisher: Cuvillier Verlag
Release Date: 2007-01-08
In this paper, an active vision system is developed which is based on image strategy. The image based control structure uses the optical flow algorithm for motion detection of an object in a visual scene. Because the optical flow is very sensitive to changes in illumination or to the quality of the video, it was necessary to use median filtering and erosion and dilatation morphological operations for the decrease of erroneous blobs residing in individual frames. Since the image coordinates of the object are subjected to noise, the Kalman filtering technique is adopted for robust estimation. A fuzzy controller based on the fuzzy condensed algorithm allows real time work for each captured frame. Finally, the proposed active vision system has been simulated in the development/simulation environment Matlab/Simulink.