Point Cloud Compression
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Point Cloud Compression
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Author : Ge Li
language : en
Publisher: Springer Nature
Release Date : 2024-05-17
Point Cloud Compression written by Ge Li and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-17 with Computers categories.
3D point clouds have broad applications across various industries and have contributed to advancements in fields such as autonomous driving, immersive media, metaverse, and cultural heritage protection. With the fast growth of 3D point cloud data and its applications, the need for efficient compression technologies has become paramount. This book delves into the forefront of point cloud compression, exploring key technologies, standardization efforts, and future prospects. This comprehensive book uncovers the foundational concepts, data acquisition methods, and datasets associated with point cloud compression. By examining the fundamental compression technologies, readers can obtain a clear understanding of prediction coding, transform coding, quantization techniques, and entropy coding. Through vivid illustrations and examples, the book elucidates how these techniques have evolved over the years and their potentials for the future. To provide a complete picture, the book presents cutting-edge research methods in point cloud compression and facilitates comparisons among them. Readers can be equipped with an in-depth understanding of the latest advancements, and can gain insights into the various approaches employed in this dynamic field. Another distinguishing aspect of this book is its exploration of standardization works for point cloud compression. Notable standards, such as MPEG G-PCC, AVS PCC, and MPEG V-PCC, are thoroughly illustrated. By delving into the methods used in geometry-based, video-based, and deep learning-based compression, readers become familiar with the latest breakthroughs in the standard communities.
Point Cloud Compression
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Author : Ge Li
language : en
Publisher: Springer
Release Date : 2024-06-12
Point Cloud Compression written by Ge Li and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-12 with Computers categories.
3D point clouds have broad applications across various industries and have contributed to advancements in fields such as autonomous driving, immersive media, metaverse, and cultural heritage protection. With the fast growth of 3D point cloud data and its applications, the need for efficient compression technologies has become paramount. This book delves into the forefront of point cloud compression, exploring key technologies, standardization efforts, and future prospects. This comprehensive book uncovers the foundational concepts, data acquisition methods, and datasets associated with point cloud compression. By examining the fundamental compression technologies, readers can obtain a clear understanding of prediction coding, transform coding, quantization techniques, and entropy coding. Through vivid illustrations and examples, the book elucidates how these techniques have evolved over the years and their potentials for the future. To provide a complete picture, the book presents cutting-edge research methods in point cloud compression and facilitates comparisons among them. Readers can be equipped with an in-depth understanding of the latest advancements, and can gain insights into the various approaches employed in this dynamic field. Another distinguishing aspect of this book is its exploration of standardization works for point cloud compression. Notable standards, such as MPEG G-PCC, AVS PCC, and MPEG V-PCC, are thoroughly illustrated. By delving into the methods used in geometry-based, video-based, and deep learning-based compression, readers become familiar with the latest breakthroughs in the standard communities.
Deep Learning For 3d Point Clouds
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Author : Wei Gao
language : en
Publisher: Springer Nature
Release Date : 2024-12-06
Deep Learning For 3d Point Clouds written by Wei Gao and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-06 with Computers categories.
As an efficient 3D vision solution, point clouds have been widely applied into diverse engineering scenarios, including immersive media communication, autonomous driving, reverse engineering, robots, topography mapping, digital twin city, medical analysis, digital museum, etc. Thanks to the great developments of deep learning theories and methods, 3D point cloud technologies have undergone fast growth during the past few years, including diverse processing and understanding tasks. Human and machine perception can be benefited from the success of using deep learning approaches, which can significantly improve 3D perception modeling and optimization, as well as 3D pre-trained and large models. This book delves into these research frontiers of deep learning-based point cloud technologies. The subject of this book focuses on diverse intelligent processing technologies for the fast-growing 3D point cloud applications, especially using deep learning-based approaches. The deep learning-based enhancement and analysis methods are elaborated in detail, as well as the pre-trained and large models with 3D point clouds. This book carefully presents and discusses the newest progresses in the field of deep learning-based point cloud technologies, including basic concepts, fundamental background knowledge, enhancement, analysis, 3D pre-trained and large models, multi-modal learning, open source projects, engineering applications, and future prospects. Readers can systematically learn the knowledge and the latest developments in the field of deep learning-based point cloud technologies. This book provides vivid illustrations and examples, and the intelligent processing methods for 3D point clouds. Readers can be equipped with an in-depth understanding of the latest advancements of this rapidly developing research field.
A Comparison Study Of Point Cloud Compression Algorithms
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Author : Mai P. Bui
language : en
Publisher:
Release Date : 2022
A Comparison Study Of Point Cloud Compression Algorithms written by Mai P. Bui and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Data compression categories.
Three-dimensional (3D) sensors, such as Light Detection and Ranging (LiDAR), stereo cameras, and radar have many applications, e.g., virtual/augmented reality (VR/AR), real-time immersive communications, and autonomous driving guidance system. The output of 3D sensors is generally represented in the form of point clouds. A point cloud consists of a set of data points. Each point has its coordinates (X, Y, Z) and associated attributes such as color in Red, Green, Blue (RGB) values. However, the volume of point cloud data generated by 3D sensors is massive. Generating a huge amount of data from point cloud addresses the storing and transmitting challenge: store the point cloud data locally on a device, share the data with other network nodes (i.e., transmit the data in wireless networks), or to manipulate and analyze the data. Therefore, effective compression schemes are needed for reducing the bandwidth of wireless networks or storage space of 3D point cloud data. This thesis aims to develop an efficient 3D point cloud stream compression benchmark that utilities several state-of-the-art 3D point clouds compression (PCC) techniques. In this study, we investigate five state-of-the-art PCC methods using five different datasets with various configurations. The objective of this study is to provide a comprehensive understanding of various approaches in PCC. The results of this paper will be helpful in developing an adaptive 3D point cloud stream compression benchmark that is efficient and benefited from different PCC techniques.
Point Cloud Compression And Low Latency Streaming
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Author : Karthik Ainala
language : en
Publisher:
Release Date : 2017
Point Cloud Compression And Low Latency Streaming written by Karthik Ainala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Data compression (Computer science) categories.
With the commoditization of the 3D depth sensors, we can now very easily model real objects and scenes into digital domain which then can be used for variety of application in gaming, animation, virtual reality, immersive communication etc. Modern sensors are capable of capturing objects with very high detail and scene of large area and thus might include millions of points. These point data usually occupy large storage space or require high bandwidth in case of real-time transmission. Thus, an efficient compression of these huge point cloud data points becomes necessary. Point clouds are often organized and compressed with octree based structures. The octree subdivision sequence is often serialized in a sequence of bytes that are subsequently entropy encoded using range coding, arithmetic coding or other methods. Such octree based algorithms are efficient only up to a certain level of detail as they have an exponential run-time in the number of subdivision levels. In addition, the compression efficiency diminishes when the number of subdivision levels increases. In this work we present an alternative way to partition the point cloud data. The point cloud is divided based on the data partition using kd tree binary division instead of Octree’s space partition method and forming a base layer. In base layer leaf nodes, the distribution of points is considered and projected to a 2D plane based on the flatness of the node points. Octree and Quadtree based partition is used to further convert the data to bitstreams. These are scalable point cloud bitstreams as we need only specific number of kd nodes in each time for a specific point of view. The use case is navigation in autonomous vehicles where it requires point cloud information up to a specific distance at different speeds. These scalable bitstreams of kd nodes can be used in real time transmission with low latency. Results show that compression performance is improved for geometry compression in point clouds and a scalable low latency streaming model is shown for navigation use case.
Image And Graphics
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Author : Huchuan Lu
language : en
Publisher: Springer Nature
Release Date : 2023-10-28
Image And Graphics written by Huchuan Lu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-28 with Computers categories.
The five-volume set LNCS 14355, 14356, 14357, 14358 and 14359 constitutes the refereed proceedings of the 12th International Conference on Image and Graphics, ICIG 2023, held in Nanjing, China, during September 22–24, 2023. The 166 papers presented in the proceedings set were carefully reviewed and selected from 409 submissions. They were organized in topical sections as follows: computer vision and pattern recognition; computer graphics and visualization; compression, transmission, retrieval; artificial intelligence; biological and medical image processing; color and multispectral processing; computational imaging; multi-view and stereoscopic processing; multimedia security; surveillance and remote sensing, and virtual reality. The ICIG 2023 is a biennial conference that focuses on innovative technologies of image, video and graphics processing and fostering innovation, entrepreneurship, and networking. It will feature world-class plenary speakers, exhibits, and high-quality peer reviewed oral and poster presentations.
Deep Learning Based Point Cloud Processing And Compression
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Author : Anique Akhtar
language : en
Publisher:
Release Date : 2022
Deep Learning Based Point Cloud Processing And Compression written by Anique Akhtar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Data compression (Computer science) categories.
A point cloud is a 3D data representation that is becoming increasingly popular. Recent significant advances in 3D sensors and capturing techniques have led to a surge in the usage of 3D point clouds in virtual reality/augmented reality (VR/AR) content creation, as well as 3D sensing for robotics, smart cities, telepresence, and automated driving applications. With an increase in point cloud applications and improved capturing technologies, we now have high-resolution point clouds with millions of points per frame. However, due to the large size of a point cloud, efficient techniques for the transmission, compression, and processing of point cloud content are still widely sought. This thesis addresses multiple issues in the transmission, compression, and processing pipeline for point cloud data. We employ a deep learning solution to process 3D dense as well as sparse point cloud data for both static as well as dynamic contents. Employing deep learning on point cloud data which is inherently sparse is a challenging task. We propose multiple deep learning-based frameworks that address each of the following problems: Point Cloud Compression Artifact Removal. V-PCC is the current state-of-the-art for dynamic point cloud compression. However, at lower bitrates, there are unpleasant artifacts introduced by V-PCC. We propose a deep learning solution for V-PCC artifact removal by leveraging the direction of projection property in V-PCC to remove quantization noise. Point Cloud Geometry Prediction. The current point cloud lossy compression and processing techniques suffer from quantization loss which results in a coarser sub-sampled representation of the point cloud. We solve the problem of points lost during voxelization by performing geometry prediction across spatial scales using deep learning architecture. Point Cloud Geometry Upsampling. Loss of details and irregularities in point cloud geometry can occur during the capturing, processing, and compression pipeline. We present a novel geometry upsampling technique, PU-Dense, which can process a diverse set of point clouds including synthetic mesh-based point clouds, real-world high-resolution point clouds, real-world indoor LiDAR scanned objects, as well as outdoor dynamically acquired LiDAR-based point clouds. Dynamic Point Cloud Interpolation. Dense photorealistic point clouds can depict real-world dynamic objects in high resolution and with a high frame rate. Frame interpolation of such dynamic point clouds would enable the distribution, processing, and compression of such content. We also propose the first point cloud interpolation framework for photorealistic dynamic point clouds. Inter-frame Compression for Dynamic Point Clouds. Efficient point cloud compression is essential for applications like virtual and mixed reality, autonomous driving, and cultural heritage. We propose a deep learning-based inter-frame encoding scheme for dynamic point cloud geometry compression. In each case, our method achieves state-of-the-art results with significant improvement to the current technologies.
Computer Vision Eccv 2022
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Author : Shai Avidan
language : en
Publisher: Springer Nature
Release Date : 2022-10-22
Computer Vision Eccv 2022 written by Shai Avidan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-22 with Computers categories.
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.
Intelligent Robotics And Applications
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Author : Xuguang Lan
language : en
Publisher: Springer Nature
Release Date : 2025-01-23
Intelligent Robotics And Applications written by Xuguang Lan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-23 with Computers categories.
The 10-volume set LNAI 15201-15210 constitutes the proceedings of the 17th International Conference on Intelligent Robotics and Applications, ICIRA 2024, which took place in Xi’an, China, during July 31–August 2, 2024. The 321 full papers included in these proceedings were carefully reviewed and selected from 489 submissions. They were organized in topical sections as follows: Part I: Innovative Design and Performance Evaluation of Robot Mechanisms. Part II: Robot Perception and Machine Learning; Cognitive Intelligence and Security Control for Multi-domain Unmanned Vehicle Systems. Part III: Emerging Techniques for Intelligent Robots in Unstructured Environment; Soft Actuators and Sensors; and Advanced Intelligent and Flexible Sensor Technologies for Robotics. Part IV: Optimization and Intelligent Control of Underactuated Robotic Systems; and Technology and application of modular robots. Part V: Advanced actuation and intelligent control in medical robotics: Advancements in Machine Vision for Enhancing Human-Robot Interaction; and Hybrid Decision-making and Control for Intelligent Robots. Part VI: Advances in Marine Robotics; Visual, Linguistic, Affective Agents: Hybrid-augmented Agents for Robotics; and Wearable Robots for Assistance, Augmentation and Rehabilitation of human movements. Part VII: Integrating World Models for Enhanced Robotic Autonomy; Advanced Sensing and Control Technologies for Intelligent Human-Robot Interaction; and Mini-Invasive Robotics for In-Situ Manipulation. Part VIII: Robot Skill Learning and Transfer; Human-Robot Dynamic System: Learning, Modelling and Control; AI-Driven Smart Industrial Systems; and Natural Interaction and Coordinated Collaboration of Robots in Dynamic Unstructured Environments. Part IX: Robotics in Cooperative Manipulation, MultiSensor Fusion, and Multi-Robot Systems; Human-machine Co-adaptive Interface; Brain inspired intelligence for robotics; Planning, control and application of bionic novel concept robots; and Robust Perception for Safe Driving. Part X: AI Robot Technology for Healthcare as a Service; Computational Neuroscience and Cognitive Models for Adaptive Human-Robot Interactions; Dynamics and Perception of Human-Robot Hybrid Systems; and Robotics for Rehabilitation: Innovations, Challenges, and Future Directions.
Image And Video Technology
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Author : Han Wang
language : en
Publisher: Springer Nature
Release Date : 2023-04-27
Image And Video Technology written by Han Wang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-27 with Computers categories.
This book constitutes the conference proceedings of the 10th Pacific Rim Symposium on Image and Video Technology, PSIVT 2022, held in Bintan Island, Indonesia, in November 2022. A total of 15 papers were carefully reviewed and selected from 18 submissions. The main conference focuses on theoretical advances or practical implementations in image and video technology.