[go: up one dir, main page]

Lv et al., 2023 - Google Patents

Research on 3D point cloud object detection methods based on deep learning

Lv et al., 2023

Document ID
15197857914507880376
Author
Lv S
Li X
Liu B
Publication year
Publication venue
2023 2nd International Conference on Big Data, Information and Computer Network (BDICN)

External Links

Snippet

As one of the fundamental directions of computer vision, object detection plays an essential role in automatic driving, image identification, and other fields. With the rapid development of artificial intelligence, deep learning applied to 3D point cloud object detection can …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6201Matching; Proximity measures
    • G06K9/6202Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/68Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10024Color image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05Geographic models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models

Similar Documents

Publication Publication Date Title
CN115880333B (en) A 3D Single-Target Tracking Method Based on Multimodal Information Fusion
US10733755B2 (en) Learning geometric differentials for matching 3D models to objects in a 2D image
Li et al. Dual-view 3d object recognition and detection via lidar point cloud and camera image
CN109597087B (en) Point cloud data-based 3D target detection method
CN110688905B (en) Three-dimensional object detection and tracking method based on key frame
Cui et al. Dense depth-map estimation based on fusion of event camera and sparse LiDAR
Du et al. ResDLPS-Net: Joint residual-dense optimization for large-scale point cloud semantic segmentation
Zhang et al. A semi-supervised 3D object detection method for autonomous driving
Hoang et al. 3ONet: 3-D detector for occluded object under obstructed conditions
CN112396655B (en) Point cloud data-based ship target 6D pose estimation method
Ouyang et al. A cgans-based scene reconstruction model using lidar point cloud
CN112950786A (en) Vehicle three-dimensional reconstruction method based on neural network
Tang et al. DFAF3D: A dual-feature-aware anchor-free single-stage 3D detector for point clouds
Hou et al. Multi-modal feature fusion for 3D object detection in the production workshop
Wu et al. Cross-regional attention network for point cloud completion
CN115908829A (en) Point column-based two-order multi-attention mechanism 3D point cloud target detection method
Lv et al. Research on 3D point cloud object detection methods based on deep learning
Li et al. Monocular 3-D object detection based on depth-guided local convolution for smart payment in D2D systems
Zhao et al. DHA: Lidar and vision data fusion-based on road object classifier
CN119313905A (en) A perception method based on lightweight real-time instance segmentation and semantic mapping
Geletu et al. Deep learning based architecture reduction on camera-lidar fusion for autonomous vehicles
CN118171186A (en) A target detection method, device, cloud device and computer device
Yang et al. Opengs-fusion: Open-vocabulary dense mapping with hybrid 3D Gaussian splatting for refined object-level understanding
CN115205578A (en) Depth-width combined classification network and corresponding point cloud classification method thereof
Zhang et al. Multiple Objects Detection based on Improved Faster R-CNN