Showing 1-25 of 4,822 resultsfor "Index Terms":Consecutive Points
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Dynamic Point Cloud Interpolation
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2022 | Conference Paper |
Cited by: Papers (7)
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. In this work, we propose a first point cloud interpolation framework for photorealistic dynamic point clouds. Given two consecutive dynamic point cloud fram...Show More
Experimental Assessment of Feature-based Lidar Odometry and Mapping
Asad Ullah Khan;Ernesto Fontana;Dario Lodi Rizzini;Stefano Caselli
2022 Sixth IEEE International Conference on Robotic Computing (IRC)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
This paper experimentally evaluates the performance of Lidar Odometry and Mapping (LOAM) algorithms based on two different features namely edges and planar surfaces. This work substitutes the LOAM current feature extraction method with novel SKIP-3D (SKeleton Interest Point 3D) which exploits the sparse Lidar point clouds obtained from 3D Lidar to extract high curvature points in the scan through ...Show More
Circular sequential k-out-of-n congestion system
IEEE Transactions on Reliability
Cited by: Papers (11)
A circular sequential k-out-of-n congestion (CSknC) model is presented. This model finds use in reliable systems to prevent single-point failure, such as (k,n) secret key sharing systems. The model assumes that each of the n servers has a known congestion probability. These n servers are arranged in a circle, and are connected sequentially. A server is connected successfully if it is not congested...Show More
DRI-LOAM: A LOAM-Based Dynamic Objects Removal Strategy Using Range Images
2023 42nd Chinese Control Conference (CCC)
Year: 2023 | Conference Paper |
The presence of dynamic points is unavoidable in scan data of urban environments, which creates unwanted traces in the map. These traces of dynamic objects may act as obstacles and thus impede good localization and navigation performances. This paper proposes a novel dynamic points removal strategy. Firstly, a LOAM based algorithm is used to generate a set of local maps. Then alignment is performe...Show More
Bi-Directional Inter-Prediction For Geometry-Based Point Cloud Compression
2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Efficient 3D point cloud compression plays critical role in immersive multimedia presentation and autonomous driving. The temporal redundancy between consecutive point cloud frames is obvious, but the exploration of inter-prediction is insufficient in the geometry-based point cloud compression (G-PCC) framework. In inter exploration model (Inter-EM) of G-PCC, the reference information can only com...Show More
Sparse Convolution Based Octree Feature Propagation for Lidar Point Cloud Compression
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Year: 2023 | Conference Paper |
Cited by: Papers (3)
With the advent of new 3D scanning technologies, point clouds have become a crucial way to depict real and virtual objects/scenes. Point clouds represent the continuous sur-faces of underlying object/scene through a collection (usually millions) of discrete, irregular, and often sparsely distributed 3D samples on the surface of the objects, e.g. LiDAR scans. This nature of point cloud data present...Show More
Application of a Depth Camera for Constructing Complex Three-Dimensional Models in Multiple Scanning Complexes
Denis V. Shilin;Svetlana I. Vtyurina;Shuvra Dey;Ilya D. Zabarin
2024 6th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)
Year: 2024 | Conference Paper |
This work provides a solution to the problem of determining camera displacement in space using 3D data analysis, specifically by searching for reference landmarks that can “stitch together” point clouds, resulting in the construction of complex objects. The solution is achieved geometrically. The reference landmarks are local maxima and convex points identified in different planes of the point clo...Show More
Lidar Odometry and Mapping Optimized by the Theory of Functional Systems in the Parking Lot
2022 International Russian Automation Conference (RusAutoCon)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
We propose a lidar odometry and mapping (LOAM) method optimized by the theory of functional system to map the parking lot and estimate the pose of the ground vehicle in real-time, providing sufficient and reliable prior information for subsequent intelligent parking. An important intelligent component in the theory of functional system is action result acceptor. The constructed action result accep...Show More
Research on Identification Method Based on Point Cloud Sequence with Millimeter-Wave Radar
2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP)
Year: 2024 | Conference Paper |
The point cloud data obtained from millimeter-wave radar has shown strong potential in pedestrian recognition tasks after tracking a target. This paper proposes a new deep learning model that can extract features from the point cloud sequence data of a target. The proposed model solves the problem of low accuracy of existing methods in pedestrian free-walking scenarios. The model's performance in ...Show More
Quantitative Reliability Assessment for 3D LiDAR Point Cloud Data Frames
Yuki Umemoto;Junya Sato;Yoshiki Yamaguchi;Taku Yamazaki;Takumi Miyoshi;Ryoichi Shinkuma
2025 IEEE International Conference on Consumer Electronics (ICCE)
Year: 2025 | Conference Paper |
Digital twin technology plays a crucial role in realizing advanced mobility services such as autonomous driving; however, it is at risk because of potential tampering with three-dimensional (3D) point cloud data collected by Light Detection And Ranging (LiDAR) systems. This paper proposes a method to detect tampering in 3D point cloud data based on LiDAR scan line characteristics and to estimate a...Show More
Sequential Point Cloud Upsampling by Exploiting Multi-Scale Temporal Dependency
In this work, we propose a new sequential point cloud upsampling method called SPU, which aims to upsample sparse, non-uniform, and orderless point cloud sequences by effectively exploiting rich and complementary temporal dependency from multiple inputs. Specifically, these inputs include a set of multi-scale short-term features from the 3D points in three consecutive frames (i.e., the previous/cu...Show More
On-the-Fly Spatio-Temporal Human Segmentation of 3D Point Cloud Data By Micro-Size LiDAR
2022 18th International Conference on Intelligent Environments (IE)
Year: 2022 | Conference Paper |
Cited by: Papers (7)
The technology of 3D recognition is evolving rapidly, enabling unprecedented growth of applications towards human-centric intelligent environments. On top of these applications human segmentation is a key technology towards analyzing and understanding human mobility in those environments. However, existing segmentation techniques rely on deep learning models, which are computationally intensive an...Show More
Graph Filter-Based Fast Motion Matching for Inter Frame Coding of MPEG G-PCC
2022 IEEE International Conference on Image Processing (ICIP)
Year: 2022 | Conference Paper |
Cited by: Papers (1)
As a key technique for geometry-based point cloud inter frame coding, motion estimation (ME) has shown the effectiveness to improve the coding efficiency. But the high complexity limits its application. We propose a novel and effective method for fast global motion matching between consecutive frames. We first divide an input point cloud into several blocks, and construct a graph for each block. T...Show More
3D Reconstruction of Edge Line by ICP-based Matching with Geometric Constraints
2020 Digital Image Computing: Techniques and Applications (DICTA)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
This paper presents a novel edge-based 3D reconstruction method using a monocular camera. The edge information is known to be illumination-invariant and to include abundant structural information in a relatively small number of pixels. However, since edge line cannot explicitly determine the pixel-to-pixel correspondence as in the feature point approach, it is difficult to perform accurate matchin...Show More
Sequential Semantic Descriptor from 3D Point Clouds for Place Recognition
2024 7th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI)
Year: 2024 | Conference Paper |
The closed-loop detection of 3D point clouds remains a significant challenge due to the complexities involved in generating effective descriptors that are robust to occlusion and viewpoint changes. Unlike most existing methods focusing on extracting local, global, and statistical features from the raw point clouds of a single frame, our approach emphasizes the utilization of semantic-level scene g...Show More
Learning Spatial-Temporal Embeddings for Sequential Point Cloud Frame Interpolation
2023 IEEE International Conference on Image Processing (ICIP)
Year: 2023 | Conference Paper |
A point cloud sequence is usually acquired at a low frame rate owing to the limitations from the sensing equipment. Consequently, the immersive experience of the virtual reality might be greatly degraded. To tackle this issue, a point cloud frame interpolation process can be used to increase the frame rate of the acquired point cloud sequence by generating new frames between the consecutive ones. ...Show More
VPU: A Video-Based Point Cloud Upsampling Framework
In this work, we propose a new patch-based framework called VPU for the video-based point cloud upsampling task by effectively exploiting temporal dependency among multiple consecutive point cloud frames, in which each frame consists of a set of unordered, sparse and irregular 3D points. Rather than adopting the sophisticated motion estimation strategy in video analysis, we propose a new spatio-te...Show More
Adaptive Fractional Open Circuit Voltage Method for Maximum Power Point Tracking in a Photovoltaic Panel
2019 32nd International Conference on VLSI Design and 2019 18th International Conference on Embedded Systems (VLSID)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
The output power of a Photovoltaic (PV) panel changes with solar insolation and temperature. Also the P-V (Power-Voltage) and I-V (Current-Voltage) characteristics of a PV cell is highly non-linear. Hence the maximum output power from the PV panel is achieved at a particular voltage (VMPP) and current (IMPP). To improve the overall efficiency, it is important to keep the PV panel to work at Maximu...Show More
Adaptive Fractional Open Circuit Voltage Method for Maximum Power Point Tracking in a Photovoltaic Panel
Year: 2019 | Conference Paper |
Design of a Backstepping-Controlled Boost Converter for MPPT in PV Chains
2019 International Conference on Advanced Electrical Engineering (ICAEE)
Year: 2019 | Conference Paper |
Cited by: Papers (5)
The objective of this work is to integrate the backstepping control for tracking the maximum power point of a photovoltaic (PV) chain. This control strategy is applied for a parallel DC-DC converter (type: boost) in order to regulate the output voltage of the PV generator, according to the reference voltage generated by the known perturb and observe (P&O) MPPT (maximum power point tracking) algori...Show More
A Modified ICP Algorithm Based on FAST and Optical Flow for 3D Registration
2022 17th Conference on Computer Science and Intelligence Systems (FedCSIS)
Year: 2022 | Conference Paper |
Cited by: Papers (2)
This paper presents a modified Iterative Closest Point (ICP) algorithm based on a suitable selection of initial points and local optical flow to speed up registration of static scenes with high accuracy. The biggest disadvantages of using standard ICP algorithm are appropriate initialization and effective matching point step in each iteration. In the proposed modification we deal with these proble...Show More
Sequential Point Clouds: A Survey
Point clouds have garnered increasing research attention and found numerous practical applications. However, many of these applications, such as autonomous driving and robotic manipulation, rely on sequential point clouds, essentially adding a temporal dimension to the data (i.e., four dimensions) because the information of the static point cloud data could provide is still limited. Recent researc...Show More
Enhancing ADAS Safety: Pedestrian Motion Classification with mmWave Radar Point Cloud
2024 31st IEEE International Conference on Electronics, Circuits and Systems (ICECS)
Year: 2024 | Conference Paper |
Early and precise pedestrian behavior recognition remains a challenge for Advanced Driver-Assistance Systems (ADAS) safety. This paper evaluates two classification methods for pedestrian motion using low-resolution 4D mmWave radar in real-world urban environments. We collected a data set of radar point cloud that captures four different types of pedestrian behavior on the road: “Walk”, “cross”, “h...Show More
Spatial-Temporal Consistency Refinement Network for Dynamic Point Cloud Frame Interpolation
2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)
Year: 2023 | Conference Paper |
Point cloud frame interpolation aims to improve the frame rate of a point cloud sequence by synthesising intermediate frames between consecutive frames. Most of the existing works only use the scene flow or features, not fully exploring their local geometry context or temporal correlation, which results in inaccurate local structural details or motion estimation. In this paper, we organically comb...Show More
Algorithm and Application of 3D Reconstruction of Deformed Pipeline Based on Point Cloud Data
Laizhen Wang;Kekuan Wang;Ruibin Duan;Yazhang He;Yinshan Ding
2023 11th International Conference on Information Technology: IoT and Smart City (ITIoTSC)
Year: 2023 | Conference Paper |
In response to the problem of three-dimensional reconstruction of submarine deformed pipelines in reverse modeling engineering, an algorithm is proposed to directly extract the characteristic parameters of submarine deformed pipelines from scattered measurement data. The first step of the algorithm is to extract feature value data from seabed deformed pipeline data, and use the feature values to f...Show More
Multi-body ICP: Motion segmentation of rigid objects on dense point clouds
2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)
Year: 2015 | Conference Paper |
Motion is one of the crucial keys for segmenting moving objects in dynamic environment. This paper proposes an approach of segmenting moving parts in the sequence of point clouds. Different rigid motions in dense point clouds are found and clustered by applying segmentation schemes such as graph-cuts into Iterative Closest Point (ICP) algorithm with initial segmentation from Generalized PCA (GPCA)...Show More
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