Haltungsverfeinerung für Multimodale Sensorintegration über Gelernte Geschwindigkeit und Kinematische Regulierung

Details

Veröffentlichungs-Nr.

EP4800431

Anmeldetag

24. Februar 2026

Veröffentlichung

2. September 2026

Rechtsraum

EP

Abstract

Synchronized camera images and radar images are captured from a scene. A shared spatial representation of the scene is generated by encoding spatial features into a spatial hash table of a shared geometry encoder. The shared spatial representation is decoded using a geometry decoder to produce camera occupancy and radar occupancy values. Camera and radar poses are refined through an optimization process that estimates per-frame pose and velocity offsets. A normal multi-layer perceptron (MLP) is used to predict surface normals at spatial locations of the scene based on the shared spatial representation, and one or more bidirectional reflectance distribution function (BRDF) bases are used to model radar reflectance. Camera density and radar density values are generated using the BRDF bases and the predicted surface normals. Predicted camera images and radar images are rendered. The shared geometry encoder is optimized based on a multimodal loss function.

Anmelder

Firmen

Robert Bosch GmbH
Carnegie Mellon University

Land

🇩🇪 Deutschland