Results 21 to 30 of about 264,137 (214)
LiDAR Point Cloud Compression by Vertically Placed Objects Based on Global Motion Prediction
IEEE Access, 2022 A point cloud acquired through a Light Detection And Ranging (LiDAR) sensor can be illustrated as a continuous frame with a time axis. Since the frame-by-frame point cloud has a high correlation between frames, a higher compression efficiency can be ...
Junsik Kim +3 more
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3D point cloud lossy compression using quadric surfaces [PDF]
PeerJ Computer Science, 2021 The presence of 3D sensors in hand-held or head-mounted smart devices has motivated many researchers around the globe to devise algorithms to manage 3D point cloud data efficiently and economically. This paper presents a novel lossy compression technique
Ulfat Imdad +3 more
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Patch Re-Segmentation and Packing for Dynamic Point Cloud Compression via Back-and-Forth Structure
IEEE Open Journal of Signal Processing, 2022 The dynamic point cloud is widely needed in 3D vision related applications such as virtual reality and telepresence. Due to the huge amount of data, a key technology before the effective application is the dynamic point cloud compression.
Haoyu Shi, Fan Li
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Prioritized Transmission Control of Point Cloud Data Obtained by LIDAR Devices
IEEE Access, 2020 Smart monitoring, particularly at intersections, is a promising service that is being considered for the concept of smart cities. A network of light detection and ranging (LIDAR) sensors, which generates point cloud data in real time, can be used to ...
Keiichiro Sato +6 more
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Cylindrical Coordinates for Lidar Point Cloud Compression [PDF]
2021 IEEE International Conference on Image Processing (ICIP), 2021 We present an efficient voxelization method to encode the geometry and attributes of 3D point clouds obtained from autonomous vehicles. Due to the circular scanning trajectory of sensors, the geometry of LiDAR point clouds is inherently different from that of point clouds captured from RGBD cameras.
Sridhara, Shashank N. +2 more
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Survey on Deep Learning-Based Point Cloud Compression
Frontiers in Signal Processing, 2022 Point clouds are becoming essential in key applications with advances in capture technologies leading to large volumes of data. Compression is thus essential for storage and transmission.
Maurice Quach +4 more
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Video-Based Point Cloud Compression Artifact Removal [PDF]
IEEE Transactions on Multimedia, 2022 Photo-realistic point cloud capture and transmission are the fundamental enablers for immersive visual communication. The coding process of dynamic point clouds, especially video-based point cloud compression (V-PCC) developed by the MPEG standardization group, is now delivering state-of-the-art performance in compression efficiency.
Anique Akhtar +5 more
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APSIPA Transactions on Signal and Information Processing, 2020 This article presents an overview of the recent standardization activities for point cloud compression (PCC). A point cloud is a 3D data representation used in diverse applications associated with immersive media including virtual/augmented reality ...
D. Graziosi +5 more
semanticscholar +1 more source
An Efficient LiDAR Point Cloud Map Coding Scheme Based on Segmentation and Frame-Inserting Network
Sensors, 2022 In this article, we present an efficient coding scheme for LiDAR point cloud maps. As a point cloud map consists of numerous single scans spliced together, by recording the time stamp and quaternion matrix of each scan during map building, we cast the ...
Qiang Wang +5 more
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Parallel Point Cloud Compression Using Truncated Octree [PDF]
2020 International Conference on Cyberworlds (CW), 2020 Existing methods of unstructured point cloud compression usually exploit the spatial sparseness of point clouds using hierarchical tree data structures for spatial encoding. However, such methods can be inefficient when very deep octrees are applied to sparse point cloud data to maintain low level of geometric error during compression.
Koh, Naimin +2 more
openaire +2 more sources