Prof. Dr. Didier Stricker
Dr. Alain Pagani
Dr. Gerd Reis
Eric Thil
Keonna Cunningham
Dr. Jason Raphael Rambach
Dr. Oliver Wasenmüller
Dr. Gabriele Bleser
Dr. Bertram Taetz
Sk Aziz Ali
Rashed Al Koutayni
Yuriy Anisimov
Jilliam Maria Diaz Barros
Ramy Battrawy
Hammad Butt
Mahdi Chamseddine
Steve Dias da Cruz
Fangwen Shu
Torben Fetzer
Michael Fürst
Christiano Couto Gava
Tewodros Amberbir Habtegebrial
Khurram Hashmi
Jigyasa Singh Katrolia
Andreas Kölsch
Onorina Kovalenko
Stephan Krauß
Paul Lesur
Muhammad Jameel Nawaz Malik
Michael Lorenz
Mina Ameli
Nareg Minaskan Karabid
Pramod Murthy
Mathias Musahl
Peter Neigel
Manthan Pancholi
María Alejandra Sánchez Marín
Dr. Kripasindhu Sarkar
Alexander Schäfer
René Schuster
Mohamed Selim
Dennis Stumpf
Yongzhi Su
Xiaoying Tan
Murad Almadani
Ahmet Firintepe
Dr. Vladislav Golyanik
Dr. Aditya Tewari
André Luiz Brandão
Time-Of-Flight Sensor Depth Enhancement for Automotive Exhaust Gas
Time-Of-Flight Sensor Depth Enhancement for Automotive Exhaust Gas
2017 IEEE International Conference on Image Processing - Proceedings IEEE International Conference on Image Processing (ICIP-2017), September 17-20, Beijing, China
- Abstract:
- The Time-of-Flight (ToF) sensor has been envisioned as a candidate of next generation sensors for intelligent vehicles. One of the problems in automotive environment is that the sensor outputs wrong values if exhaust gas exists in the scene. In this paper, we provide two new contributions to the signal processing aspects of the ToF sensor for automotive use. First, we present the sensor characteristics and models for exhaust gas to cope with them. Second, we develop a depth enhance- ment algorithm to reject the influence of exhaust gas from multiple images. Experimental results demonstrate the effec- tiveness of the depth enhancement algorithm for both static data (including ground truth) and on-vehicle data acquired by the sensor mounted on a car.