Multimodal Scene Understanding: Algorithms, Applications and Deep Learning

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry, providing the latest algorithms and applications that involve combining multiple sources of information. Uniquely, it 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, helping to foster interdisciplinary interaction and collaboration between them. It will be very relevant to 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. Contains State-of-the-art development on multi-modal computingA focus on algorithms and applicationsGives novel deep learning topics on multi-sensor fusionPresents Multi-modal deep learning INDICE: 1. Fusion of Visual and Inertial Information in SLAM Algorithms 2. 3D scene reconstruction and interpretation from multi-sensor imagery 3. Multi-modal and cross-domain analysis of scenes for the understanding of the geographic iconographic heritage 4. Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection 5. Learning a Fully Convolutional Network for Object Recognition using very few Data 6. On calibration of a sensor box with multiple sensors 7. Assigning tie points to a generalised building model for use image orientation 8. Visual-inertial motion tracking device for embedded systems 9. Decision fusion of remote sensing data for land cover classification: application to very high spatial resolution multispectral images and spectral/temporal rich data 10. Co-training using different modalities

• ISBN: 978-0-12-817358-9
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 525
• Fecha Publicación: 01/08/2019
• Nº Volúmenes: 1
• Idioma: Inglés