KEYWORDS: 3D modeling, Image segmentation, 3D image processing, 3D image reconstruction, Visual process modeling, Systems modeling, 3D metrology, Performance modeling, Clouds, Neural networks
imultaneous 3D scene reconstruction and semantic segmentation are required in many applications such as autonomous driving, robotics, and optical metrology. Classic 3D reconstruction methods usually perform such operations twofold. Firstly, a 3D scanner or laser scanner acquires a point cloud. Secondly, semantic segmentation of the point cloud is performed. Recently a new kind of 3D model representation was proposed that utilizes the trapezium-shaped voxels that are aligned with the camera’s frustum and pixels [1]. Frustum voxel models proved to be effective for monocular 3D scene reconstruction and segmentation from monocular images [2]. Still, many existing 3D scanning systems readily provide stereo cameras. The performance of frustum voxel model-based methods for stereo input remains an open question. This paper is focused on the evaluation of the 3D reconstruction quality of a volumetric neural network with a monocular and stereo input. We leverage an SSZ [2] volumetric neural network as a starting point for our research. We develop its modified version that we term Stereo-SSZ that receives a stereo pair as an input. We compare the performance of the original SSZ model and our Stereo-SSZ model on different real and synthetic 3D shape datasets. Specifically, we generate a stereo version of the SemanticVoxels [2] dataset and capture stereo pairs of multiple real objects using a structured light scanner. The results of our experiments are encouraging and demonstrate that the model with a stereo input outperforms the original monocular SSZ network. Specifically, the frustum voxel models generated by our Stereo-SSZ model have lower surface distance errors and demonstrate fine details in the reconstructed 3D models.
Hydrodynamic tunnel is an effective mean for studying wing flow process in aerodynamics and hydrodynamics. It allows to study flow characteristics in controlled conditions and to model the conditions that could not be studied in real flight, such as aerodynamic characteristics at critical angles of attack, in icing conditions etc. Techniques for flow visualisation such as coloured jets or small particles allow to have a qualitative data about flow behaviour, being the valuable means for understanding flow behaviour. But it is more important to have quantitative characteristics of the flow allowing to predict the process evolution and to develop safety measures and recommendations.
The presented study addresses to developing a system for optical 3D measurements in hydrodynamic tunnel basing on photogrammetric techniques. To provide accurate measurements in condition of two optical media interfaces (air-glass and air-liquid) the accurate model of image formation accounting refraction is developed.
The developed photogrammetric system includes several high speed cameras (from 2 to 4 cameras) mounted in a fixed position relatively the working space and a structured light projector. Original technique is applied for the system calibration.
Two metrics has been used as a measure of the accuracy of the calibration: the first one being based on the test field points measurements, and the second one using points-to points distance for the surfaces of a reference object.
The key contributions of this paper are: (1) accurate model of image formation in case of several media interfaces (2) a technique for photogrammetric system calibration for 3D measurements in hydrodynamic tunnel (3) experimental evaluation of calibration accuracy for multi-media 3D measurements.
The performed experimental evaluation of the developed photogrammetric system has proved high accuracy of system calibration and optical 3D measurements in multi-media optical environment. The developed technique for photogrammetric system calibration and 3D measurements demonstrated applicability for the task of 3D flow analysis in hydrodynamic tunnel.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.