In various examples, a single camera is used to capture two images of a scene from different locations. A trained neural network, taking the two images as inputs, outputs a scene structure map that indicates a ratio of height and depth values for pixel locations associated with the images. This ratio may indicate the presence of an object above a surface (e.g., road surface) within the scene. Object detection then can be performed on non-zero values or regions within the scene structure map.
OBJECT DETECTION USING PLANAR HOMOGRAPHY AND SELF-SUPERVISED SCENE STRUCTURE UNDERSTANDING
2024-02-08
Patent
Electronic Resource
English
IPC: | G06T Bilddatenverarbeitung oder Bilddatenerzeugung allgemein , IMAGE DATA PROCESSING OR GENERATION, IN GENERAL / B60R Fahrzeuge, Fahrzeugausstattung oder Fahrzeugteile, soweit nicht anderweitig vorgesehen , VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V / H04N PICTORIAL COMMUNICATION, e.g. TELEVISION , Bildübertragung, z.B. Fernsehen |
Object detection using planar homography and self-supervised scene structure understanding
European Patent Office | 2023
|OBJECT DETECTION USING PLANAR HOMOGRAPHY AND SELF-SUPERVISED SCENE STRUCTURE UNDERSTANDING
European Patent Office | 2021
|Planar homography: accuracy analysis and applications
IEEE | 2005
|Planar Homography: Accuracy Analysis and Applications
British Library Conference Proceedings | 2005
|Infinite Homography Estimation Using Two Arbitrary Planar Rectangles
Springer Verlag | 2006
|