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1. Three-dimensional fluid–structure interaction diagnostics using a single camera

   Sapkota, Bibek; Mettelsiefen, Holger; Raghav, Vrishank; Thurow, Brian S (October 2025, Journal of fluids and structures)

   A new method for fluid–structure interaction (FSI) diagnostics to simultaneously capture time-resolved three-dimensional, three-component (3D3C) velocity fields and structural deformations using a single light field camera is presented. A light field camera encodes both spatial and angular information of light rays collected by a conventional imaging lens that allows for the 3D reconstruction of a scene from a single image. Building upon this capability, a light field fluid–structure interaction (LF FSI) methodology is developed with a focus on experimental scenarios with low optical access. Proper orthogonal decomposition (POD) is used to separate particle and surface information contained in the same image. A correlation-based depth estimation technique is introduced to reconstruct instantaneous surface positions from the disparity between angular perspectives and conventional particle image velocimetry (PIV) is used for flow field reconstruction. Validation of the methodology is achieved using synthetic images of simultaneously moving flat plates and a vortex ring with a small increase in uncertainty under ~0.5 microlenses observed in both flow and structure measurement compared to independent measurements. The method is experimentally verified using a flat plate translating along the camera’s optical axis in a flow field with varying particle concentrations. Finally, simultaneous reconstructions of the flow field and surface shape around a flexible membrane are presented, with the surface reconstruction further validated using simultaneously captured stereo images. The findings indicate that the LF FSI methodology provides a new capability to simultaneously measure large-scale flow characteristics and structural deformations using a single camera. 

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2. Phase- shifted 3D Imaging of Rotating Milling/Drilling tools

   Guo, Xiangyu; Lee, ChaBum (October 2020, American Society for Precision Engineering)

   null (Ed.)

   Drilling and milling operations are material removal processes involved in everyday conventional productions, especially in the high-speed metal cutting industry. The monitoring of tool information (wear, dynamic behavior, deformation, etc.) is essential to guarantee the success of product fabrication. Many methods have been applied to monitor the cutting tools from the information of cutting force, spindle motor current, vibration, as well as sound acoustic emission. However, those methods are indirect and sensitive to environmental noises. Here, the in-process imaging technique that can capture the cutting tool information while cutting the metal was studied. As machinists judge whether a tool is worn-out by the naked eye, utilizing the vision system can directly present the performance of the machine tools. We proposed a phase shifted strobo-stereoscopic method (Figure 1) for three-dimensional (3D) imaging. The stroboscopic instrument is usually applied for the measurement of fast-moving objects. The operation principle is as follows: when synchronizing the frequency of the light source illumination and the motion of object, the object appears to be stationary. The motion frequency of the target is transferring from the count information of the encoder signals from the working rotary spindle. If small differences are added to the frequency, the object appears to be slowly moving or rotating. This effect can be working as the source for the phase-shifting; with this phase information, the target can be whole-view 3D reconstructed by 360 degrees. The stereoscopic technique is embedded with two CCD cameras capturing images that are located bilateral symmetrically in regard to the target. The 3D scene is reconstructed by the location information of the same object points from both the left and right images. In the proposed system, an air spindle was used to secure the motion accuracy and drilling/milling speed. As shown in Figure 2, two CCDs with 10X objective lenses were installed on a linear rail with rotary stages to capture the machine tool bit raw picture for further 3D reconstruction. The overall measurement process was summarized in the flow chart (Figure 3). As the count number of encoder signals is related to the rotary speed, the input speed (unit of RPM) was set as the reference signal to control the frequency (f0) of the illumination of the LED. When the frequency was matched with the reference signal, both CCDs started to gather the pictures. With the mismatched frequency (Δf) information, a sequence of images was gathered under the phase-shifted process for a whole-view 3D reconstruction. The study in this paper was based on a 3/8’’ drilling tool performance monitoring. This paper presents the principle of the phase-shifted strobe-stereoscopic 3D imaging process. A hardware set-up is introduced, , as well as the 3D imaging algorithm. The reconstructed image analysis under different working speeds is discussed, the reconstruction resolution included. The uncertainty of the imaging process and the built-up system are also analyzed. As the input signal is the working speed, no other information from other sources is required. This proposed method can be applied as an on-machine or even in-process metrology. With the direct method of the 3D imaging machine vision system, it can directly offer the machine tool surface and fatigue information. This presented method can supplement the blank for determining the performance status of the machine tools, which further guarantees the fabrication process. 

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3. Self-supervised Depth Estimation from Spectral Consistency and Novel View Synthesis

   Yawen Lu, Guoyu Lu (January 2022, IEEE International Joint Conference on Neural Network (IJCNN))

   Single image depth estimation is a critical issue for robot vision, augmented reality, and many other applications when an image sequence is not available. Self-supervised single image depth estimation models target at predicting accurate disparity map just from one single image without ground truth supervision or stereo image pair during real applications. Compared with direct single image depth estimation, single image stereo algorithm can generate the depth from different camera perspectives. In this paper, we propose a novel architecture to infer accurate disparity by leveraging both spectral-consistency based learning model and view-prediction based stereo reconstruction algorithm. Direct spectral-consistency based method can avoid false positive matching in smooth regions. Single image stereo can preserve more distinct boundaries from another camera perspective. By learning confidence maps and designing a fusion strategy, the two disparities from the two approaches are able to be effectively fused to produce the refined disparity. Extensive experiments and ablations indicate that our method exploits both advantages of spectral consistency and view prediction, especially in constraining object boundaries and correcting wrong predicting regions. 

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4. Multicamera 3D Reconstruction of Dynamic Surgical Cavities: Camera Grouping and Pair Sequencing

   https://doi.org/10.1109/ISMR.2019.8710190  

   Su, Yun-Hsuan; Huang, Kevin; Hannaford, Blake (April 2019, 2019 International Symposium on Medical Robotics (ISMR), Atlanta, GA, USA, 2019)

   null (Ed.)

   Dynamic 3D reconstruction of surgical cavities is essential in a wide range of computer-assisted surgical intervention applications, including but not limited to surgical guidance, pre-operative image registration and vision-based force estimation. According to a survey on vision based 3D reconstruction for abdominal minimally invasive surgery (MIS) [1], real-time 3D reconstruction and tissue deformation recovery remain open challenges to researchers. The main challenges include specular reflections from the wet tissue surface and the highly dynamic nature of abdominal surgical scenes. This work aims to overcome these obstacles by using multiple viewpoint and independently moving RGB cameras to generate an accurate measurement of tissue deformation at the volume of interest (VOI), and proposes a novel efficient camera pairing algorithm. Experimental results validate the proposed camera grouping and pair sequencing, and were evaluated with the Raven-II [2] surgical robot system for tool navigation, the Medtronic Stealth Station s7 surgical navigation system for real- time camera pose monitoring, and the Space Spider white light scanner to derive the ground truth 3D model. 

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5. Static coded aperture in robotic X-ray tomography systems

   https://doi.org/10.1364/OE.449505  

   Mao, Tianyi; Ma, Xu; Cuadros, Angela_P; Dai, XiuBin; Wang, Zhiteng; Zhang, Xin; Zhu, Shujin; Zhu, Jianjian; Arce, Gonzalo_R (February 2022, Optics Express)

   Coded aperture X-ray computed tomography is a computational imaging technique capable of reconstructing inner structures of an object from a reduced set of X-ray projection measurements. Coded apertures are placed in front of the X-ray sources from different views and thus significantly reduce the radiation dose. This paper introduces coded aperture X-ray computed tomography for robotic X-ray systems which offer positioning flexibility. While single coded-aperture 3D tomography was recently introduced for standard trajectory CT scanning, it is shown that significant gains in imaging performance can be attained by simple modifications in the CT scanning trajectories enabled by emerging dual robotic CT systems. In particular, the subject is fixed on a plane and the CT system uniformly rotates around ther −axis which is misaligned with the coordinate axes. A single stationary coded aperture is placed on front of the robotic X-ray source above the plane and the corresponding X-ray projections are measured by a two-dimensional detector on the second arm of the robotic system. The compressive measurements with misalignment enable the reconstruction of high-resolution three-dimensional volumetric images from the low-resolution coded projections on the detector at a sub-sampling rate. An efficient algorithm is proposed to generate the rotation matrix with two basic sub-matrices and thus the forward model is formulated. The stationary coded aperture is designed based on the Pearson product-moment correlation coefficient analysis and the direct binary search algorithm is used to obtain the optimized coded aperture. Simulations using simulated datasets show significant gains in reconstruction performance compared to conventional coded aperture CT systems. 

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