[go: up one dir, main page]

Kiefer, 2023 - Google Patents

Leveraging metadata for computer vision on unmanned aerial vehicles

Kiefer, 2023

View PDF
Document ID
7336681375204329940
Author
Kiefer B
Publication year

External Links

Snippet

The integration of computer vision technology into Unmanned Aerial Vehicles (UAVs) has become increasingly crucial in various aerial vision-based applications. Despite the great significant success of generic computer vision methods, a considerable performance drop is …
Continue reading at bibliographie.uni-tuebingen.de (PDF) (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
    • 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
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • 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
    • G06K9/20Image acquisition
    • G06K9/32Aligning or centering of the image pick-up or image-field
    • G06K9/3233Determination of region of interest
    • 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
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Varga et al. Seadronessee: A maritime benchmark for detecting humans in open water
Ramachandran et al. A review on object detection in unmanned aerial vehicle surveillance.
Bondi et al. BIRDSAI: A dataset for detection and tracking in aerial thermal infrared videos
Zhang et al. CAD-Net: A context-aware detection network for objects in remote sensing imagery
US11227191B2 (en) Conditional loss function modification in a neural network
US11232330B2 (en) Adaptive neural network selection to extract particular results
Wu et al. Multivehicle object tracking in satellite video enhanced by slow features and motion features
Mou et al. Multitemporal very high resolution from space: Outcome of the 2016 IEEE GRSS data fusion contest
Kiefer et al. 1st workshop on maritime computer vision (macvi) 2023: Challenge results
Nguyen et al. The state of aerial surveillance: A survey
US12430892B2 (en) Detecting an object in an image using multiband and multidirectional filtering
Huszár et al. Live spoofing detection for automatic human activity recognition applications
CN110631588A (en) A UAV visual navigation and positioning method based on RBF network
Carrio et al. Attitude estimation using horizon detection in thermal images
Lee et al. Caltech aerial rgb-thermal dataset in the wild
CN112487892A (en) Unmanned aerial vehicle ground detection method and system based on confidence
EP2517152B1 (en) Method of object classification in an image observation system
Goyal et al. Improving Accuracy of Object Detection in Autonomous Drones with Convolutional Neural Networks
Huang et al. Single target tracking in high-resolution satellite videos: a comprehensive review
Zhao et al. Multi-sensor fusion-driven surface vessel identification and tracking using unmanned aerial vehicles for maritime surveillance
Wu et al. Multimodal collaboration networks for geospatial vehicle detection in dense, occluded, and large-scale events
Montanari et al. Ground vehicle detection and classification by an unmanned aerial vehicle
Ye et al. More Clear, More Flexible, More Precise: A Comprehensive Oriented Object Detection benchmark for UAV
Truong et al. Rotated mask region-based convolutional neural network detection for parking space management system
Kiefer Leveraging metadata for computer vision on unmanned aerial vehicles