Multimodal Scene Understanding PDF Download
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Author | : Michael Yang |
Publisher | : Academic Press |
Total Pages | : 422 |
Release | : 2019-07-16 |
Genre | : Computers |
ISBN | : 0128173599 |
Download Multimodal Scene Understanding Book in PDF, ePub and Kindle
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
Author | : Boris Schauerte |
Publisher | : |
Total Pages | : |
Release | : 2014 |
Genre | : |
ISBN | : |
Download Multimodal Computational Attention for Scene Understanding Book in PDF, ePub and Kindle
Author | : Boris Schauerte |
Publisher | : Springer |
Total Pages | : 220 |
Release | : 2016-05-11 |
Genre | : Technology & Engineering |
ISBN | : 3319337963 |
Download Multimodal Computational Attention for Scene Understanding and Robotics Book in PDF, ePub and Kindle
This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.
Author | : Yifei Zhang |
Publisher | : |
Total Pages | : 114 |
Release | : 2021 |
Genre | : |
ISBN | : |
Download Real-time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation Book in PDF, ePub and Kindle
Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptively learn the joint representations of modality-specific features and reduce model uncertainty via statistical post-processing.In the case of semi-supervised semantic scene understanding, we first proposed a novel few-shot segmentation method based on the prototypical network, which employs multiscale feature enhancement and the attention mechanism. Then we extended the RGB-centric algorithms to take advantage of supplementary depth cues. Comprehensive empirical evaluations on different benchmark datasets demonstrate that all the proposed algorithms achieve superior performance in terms of accuracy as well as demonstrating the effectiveness of complementary modalities for outdoor scene understanding for autonomous navigation.
Author | : Yifei Zhang |
Publisher | : |
Total Pages | : 0 |
Release | : 2021 |
Genre | : |
ISBN | : |
Download Real-time Multimodal Semantic Scene Understanding for Autonomous UGV Navigation Book in PDF, ePub and Kindle
Robust semantic scene understanding is challenging due to complex object types, as well as environmental changes caused by varying illumination and weather conditions. This thesis studies the problem of deep semantic segmentation with multimodal image inputs. Multimodal images captured from various sensory modalities provide complementary information for complete scene understanding. We provided effective solutions for fully-supervised multimodal image segmentation and few-shot semantic segmentation of the outdoor road scene. Regarding the former case, we proposed a multi-level fusion network to integrate RGB and polarimetric images. A central fusion framework was also introduced to adaptively learn the joint representations of modality-specific features and reduce model uncertainty via statistical post-processing.In the case of semi-supervised semantic scene understanding, we first proposed a novel few-shot segmentation method based on the prototypical network, which employs multiscale feature enhancement and the attention mechanism. Then we extended the RGB-centric algorithms to take advantage of supplementary depth cues. Comprehensive empirical evaluations on different benchmark datasets demonstrate that all the proposed algorithms achieve superior performance in terms of accuracy as well as demonstrating the effectiveness of complementary modalities for outdoor scene understanding for autonomous navigation.
Author | : Dana Kulić |
Publisher | : Springer |
Total Pages | : 858 |
Release | : 2017-03-20 |
Genre | : Technology & Engineering |
ISBN | : 3319501151 |
Download 2016 International Symposium on Experimental Robotics Book in PDF, ePub and Kindle
Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain at the center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.
Author | : Xavier Alameda-Pineda |
Publisher | : Academic Press |
Total Pages | : 498 |
Release | : 2018-11-13 |
Genre | : Computers |
ISBN | : 0128146028 |
Download Multimodal Behavior Analysis in the Wild Book in PDF, ePub and Kindle
Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data
Author | : Dürr, Fabian |
Publisher | : KIT Scientific Publishing |
Total Pages | : 248 |
Release | : 2023-10-09 |
Genre | : |
ISBN | : 3731513145 |
Download Multimodal Panoptic Segmentation of 3D Point Clouds Book in PDF, ePub and Kindle
The understanding and interpretation of complex 3D environments is a key challenge of autonomous driving. Lidar sensors and their recorded point clouds are particularly interesting for this challenge since they provide accurate 3D information about the environment. This work presents a multimodal approach based on deep learning for panoptic segmentation of 3D point clouds. It builds upon and combines the three key aspects multi view architecture, temporal feature fusion, and deep sensor fusion.
Author | : Jeannette Bohg |
Publisher | : |
Total Pages | : |
Release | : 2011 |
Genre | : |
ISBN | : |
Download Multi-Modal Scene Understanding for Robotic Grasping Book in PDF, ePub and Kindle
Author | : Andrei Popescu-Belis |
Publisher | : Springer |
Total Pages | : 318 |
Release | : 2008-02-22 |
Genre | : Computers |
ISBN | : 3540781552 |
Download Machine Learning for Multimodal Interaction Book in PDF, ePub and Kindle
This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic, in June 2007. The 25 revised full papers presented together with 1 invited paper were carefully selected during two rounds of reviewing and revision from 60 workshop presentations. The papers are organized in topical sections on multimodal processing, HCI, user studies and applications, image and video processing, discourse and dialogue processing, speech and audio processing, as well as the PASCAL speech separation challenge.