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1. Non-reciprocal acoustics in a viscous environment

   https://doi.org/10.1098/rspa.2020.0657  

   Heo, Hyeonu; Walker, Ezekiel; Zubov, Yurii; Shymkiv, Dmitrii; Wages, Dylan; Krokhin, Arkadii; Choi, Tae-Youl; Neogi, Arup (December 2020, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences)

   null (Ed.)

   It is demonstrated that acoustic transmission through a phononic crystal with anisotropic solid scatterers becomes non-reciprocal if the background fluid is viscous. In an ideal (inviscid) fluid, the transmission along the direction of broken P symmetry is asymmetric. This asymmetry is compatible with reciprocity since time-reversal symmetry ( T symmetry) holds. Viscous losses break T symmetry, adding a non-reciprocal contribution to the transmission coefficient. The non-reciprocal transmission spectra for a phononic crystal of metallic circular cylinders in water are experimentally obtained and analysed. The surfaces of the cylinders were specially processed in order to weakly break P symmetry and increase viscous losses through manipulation of surface features. Subsequently, the non-reciprocal part of transmission is separated from its asymmetric reciprocal part in numerically simulated transmission spectra. The level of non-reciprocity is in agreement with the measure of broken P symmetry. The reported study contradicts commonly accepted opinion that linear dissipation cannot be a reason leading to non-reciprocity. It also opens a way for engineering passive acoustic diodes exploring the natural viscosity of any fluid as a factor leading to non-reciprocity. 

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2. Snapshot polarimetric diffuse-specular separation

   https://doi.org/10.1364/OE.460984  

   Dave, Akshat; Hold-Geoffroy, Yannick; Hašan, Miloš; Sunkavalli, Kalyan; Veeraraghavan, Ashok (September 2022, Optics Express)

   We present a polarization-based approach to perform diffuse-specular separation from a single polarimetric image, acquired using a flexible, practical capture setup. Our key technical insight is that, unlike previous polarization-based separation methods that assume completely unpolarized diffuse reflectance, we use a more general polarimetric model that accounts for partially polarized diffuse reflections. We capture the scene with a polarimetric sensor and produce an initial analytical diffuse-specular separation that we further pass into a deep network trained to refine the separation. We demonstrate that our combination of analytical separation and deep network refinement produces state-of-the-art diffuse-specular separation, which enables image-based appearance editing of dynamic scenes and enhanced appearance estimation. 

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3. 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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4. End-to-End 3D Face Reconstruction with Expressions and Specular Albedos from Single In-the-wild Images

   https://doi.org/10.1145/3503161.3547800  

   Deng, Qixin; Le, Binh H.; Jin, Aobo; Deng, Zhigang (October 2022, Proceeding of ACM International Conference on Multimedia 2022)

   Recovering 3D face models from in-the-wild face images has numerous potential applications. However, properly modeling complex lighting effects in reality, including specular lighting, shadows, and occlusions, from a single in-the-wild face image is still considered as a widely open research challenge. In this paper, we propose a convolutional neural network based framework to regress the face model from a single image in the wild. The outputted face model includes dense 3D shape, head pose, expression, diffuse albedo, specular albedo, and the corresponding lighting conditions. Our approach uses novel hybrid loss functions to disentangle face shape identities, expressions, poses, albedos, and lighting. Besides a carefully designed ablation study, we also conduct direct comparison experiments to show that our method can outperform state-of-art methods both quantitatively and qualitatively. 

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5. Thermal Non-Line-of-Sight Imaging

   https://doi.org/10.1109/ICCPHOT.2019.8747343  

   Maeda, Tomohiro; Wang, Yiqin; Raskar, Ramesh; Kadambi, Achuta (May 2019, IEEE International Conference on Computational Photography)

   We propose a novel non-line-of-sight (NLOS) imaging framework with long-wave infrared (IR). At long-wave IR wavelengths, certain physical parameters are more favorable for high-fidelity reconstruction. In contrast to prior work in visible light NLOS, at long-wave IR wavelengths, the hidden heat source acts as a light source. This simplifies the problem to a single bounce problem. In addition, surface reflectance has a much stronger specular reflection in the long-wave IR spectrum than in the visible light spectrum. We reformulate a light transport model that leverages these favorable physical properties of long-wave IR. Specifically, we demonstrate 2D shape recovery and 3D localization of a hidden object. Furthermore, we demonstrate near real-time and robust NLOS pose estimation of a human figure, the first such demonstration, to our knowledge. 

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