Calibration and Sensitivity Analysis of a Stereo Vision-Based Driver Assistance System

Az http://intechweb.org/ alatti "Books" fül alatt kell rákeresni a "Stereo Vision" címre és az 1. fejezetre

Evaluation of CNN-based Single-Image Depth Estimation Methods

While an increasing interest in deep models for single-image depth estimation methods can be observed, established schemes for their evaluation are still limited. We propose a set of novel quality criteria, allowing for a more detailed analysis by focusing on specific characteristics of depth maps. In particular, we address the preservation of edges and planar regions, depth consistency, and absolute distance accuracy. In order to employ these metrics to evaluate and compare state-of-the-art single-image depth estimation approaches, we provide a new high-quality RGB-D dataset. We used a DSLR camera together with a laser scanner to acquire high-resolution images and highly accurate depth maps. Experimental results show the validity of our proposed evaluation protocol

Stereo Matching in the Presence of Sub-Pixel Calibration Errors

Stereo matching commonly requires rectified images that are computed from calibrated cameras. Since all under-lying parametric camera models are only approximations, calibration and rectification will never be perfect. Additionally, it is very hard to keep the calibration perfectly stable in application scenarios with large temperature changes and vibrations. We show that even small calibration errors of a quarter of a pixel are severely amplified on certain structures. We discuss a robotics and a driver assistance example where sub-pixel calibration errors cause severe problems. We propose a filter solution based on signal theory that removes critical structures and makes stereo algorithms less sensitive to calibration errors. Our approach does not aim to correct decalibration, but rather to avoid amplifications and mismatches. Experiments on ten stereo pairs with ground truth and simulated decalibrations as well as images from robotics and driver assistance scenarios demonstrate the success and limitations of our solution that can be combined with any stereo method

Accurate Telescope Mount Positioning with MEMS Accelerometers

This paper describes the advantages and challenges of applying microelectromechanical accelerometer systems (MEMS accelerometers) in order to attain precise, accurate and stateless positioning of telescope mounts. This provides a completely independent method from other forms of electronic, optical, mechanical or magnetic feedback or real-time astrometry. Our goal is to reach the sub-arcminute range which is well smaller than the field-of-view of conventional imaging telescope systems. Here we present how this sub-arcminute accuracy can be achieved with very cheap MEMS sensors and we also detail how our procedures can be extended in order to attain even finer measurements. In addition, our paper discusses how can a complete system design be implemented in order to be a part of a telescope control system.Comment: Accepted for publication in PASP, 12 page