3 citations · 5 across the 3 of their papers we have counts for
6 papers
SD-6DoF-ICLK: Sparse and Deep Inverse Compositional Lucas-Kanade Algorithm on SE(3)
Timo Hinzmann, Roland Siegwart
This paper introduces SD-6DoF-ICLK, a learning-based Inverse Compositional Lucas-Kanade (ICLK) pipeline that uses sparse depth information to optimize the relative pose that best a…
Deep UAV Localization with Reference View Rendering
Timo Hinzmann, Roland Siegwart
This paper presents a framework for the localization of Unmanned Aerial Vehicles (UAVs) in unstructured environments with the help of deep learning. A real-time rendering engine is…
Deep Learning-based Human Detection for UAVs with Optical and Infrared Cameras: System and Experiments
Timo Hinzmann, Tobias Stegemann, Cesar Cadena +1
In this paper, we present our deep learning-based human detection system that uses optical (RGB) and long-wave infrared (LWIR) cameras to detect, track, localize, and re-identify h…
Flexible Trinocular: Non-rigid Multi-Camera-IMU Dense Reconstruction for UAV Navigation and Mapping
Timo Hinzmann, Cesar Cadena, Juan Nieto +1
In this paper, we propose a visual-inertial framework able to efficiently estimate the camera poses of a non-rigid trinocular baseline for long-range depth estimation on-board a fa…
Cubic Range Error Model for Stereo Vision with Illuminators
Marius Huber, Timo Hinzmann, Roland Siegwart +1
Use of low-cost depth sensors, such as a stereo camera setup with illuminators, is of particular interest for numerous applications ranging from robotics and transportation to mixe…
Free LSD: Prior-Free Visual Landing Site Detection for Autonomous Planes
Timo Hinzmann, Thomas Stastny, Cesar Cadena +2
Full autonomy for fixed-wing unmanned aerial vehicles (UAVs) requires the capability to autonomously detect potential landing sites in unknown and unstructured terrain, allowing fo…