Year: 2024
Type: conference-paper
Abstract: Inverse perspective mapping (IPM) is a crucial technique in camera-based autonomous driving, transforming the perspective view captured by the camera into a bird’s-eye view. This can be beneficial for accurate environmental perception, path planning, obstacle detection, and navigation. IPM faces challenges such as distortion and inaccuracies due to varying road inclinations and intrinsic camera properties. Herein, we revealed inaccuracies inherent in our current IPM approach so proper correction techniques can be applied later. We aimed to explore correction possibilities to enhance the accuracy of IPM and examine other methods that could be used as a benchmark or even a replacement, such as stereo vision and deep learning-based monocular depth estimation methods. With this work, we aimed to provide an analysis and direction for working with IPM.
Authors: Norbert Markó, Péter Kőrös, Miklós Unger
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Funder: European Commission
Award: G424312806
OpenAlex ID: W4404192446