反射マップを用いた非ランバート面の３次元形状復元

京都大学新制・課程博士博士(情報学)甲第25421号情博第859号京都大学大学院情報学研究科知能情報学専攻(主査)教授 西野 恒, 教授 西田 眞也, 教授 河原 達也学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

Correspondences of the Third Kind: Camera Pose Estimation from Object Reflection

Computer vision has long relied on two kinds of correspondences: pixel correspondences in images and 3D correspondences on object surfaces. Is there another kind, and if there is, what can they do for us? In this paper, we introduce correspondences of the third kind we call reflection correspondences and show that they can help estimate camera pose by just looking at objects without relying on the background. Reflection correspondences are point correspondences in the reflected world, i.e., the scene reflected by the object surface. The object geometry and reflectance alters the scene geometrically and radiometrically, respectively, causing incorrect pixel correspondences. Geometry recovered from each image is also hampered by distortions, namely generalized bas-relief ambiguity, leading to erroneous 3D correspondences. We show that reflection correspondences can resolve the ambiguities arising from these distortions. We introduce a neural correspondence estimator and a RANSAC algorithm that fully leverages all three kinds of correspondences for robust and accurate joint camera pose and object shape estimation just from the object appearance. The method expands the horizon of numerous downstream tasks, including camera pose estimation for appearance modeling (e.g., NeRF) and motion estimation of reflective objects (e.g., cars on the road), to name a few, as it relieves the requirement of overlapping background

DeepShaRM: Multi-View Shape and Reflectance Map Recovery Under Unknown Lighting

Geometry reconstruction of textureless, non-Lambertian objects under unknown natural illumination (i.e., in the wild) remains challenging as correspondences cannot be established and the reflectance cannot be expressed in simple analytical forms. We derive a novel multi-view method, DeepShaRM, that achieves state-of-the-art accuracy on this challenging task. Unlike past methods that formulate this as inverse-rendering, i.e., estimation of reflectance, illumination, and geometry from images, our key idea is to realize that reflectance and illumination need not be disentangled and instead estimated as a compound reflectance map. We introduce a novel deep reflectance map estimation network that recovers the camera-view reflectance maps from the surface normals of the current geometry estimate and the input multi-view images. The network also explicitly estimates per-pixel confidence scores to handle global light transport effects. A deep shape-from-shading network then updates the geometry estimate expressed with a signed distance function using the recovered reflectance maps. By alternating between these two, and, most important, by bypassing the ill-posed problem of reflectance and illumination decomposition, the method accurately recovers object geometry in these challenging settings. Extensive experiments on both synthetic and real-world data clearly demonstrate its state-of-the-art accuracy.Comment: 3DV 202

Learning from AI: An Interactive Learning Method Using a DNN Model Incorporating Expert Knowledge as a Teacher

Visual explanation is an approach for visualizing the grounds of judgment by deep learning, and it is possible to visually interpret the grounds of a judgment for a certain input by visualizing an attention map. As for deep-learning models that output erroneous decision-making grounds, a method that incorporates expert human knowledge in the model via an attention map in a manner that improves explanatory power and recognition accuracy is proposed. In this study, based on a deep-learning model that incorporates the knowledge of experts, a method by which a learner "learns from AI" the grounds for its decisions is proposed. An "attention branch network" (ABN), which has been fine-tuned with attention maps modified by experts, is prepared as a teacher. By using an interactive editing tool for the fine-tuned ABN and attention maps, the learner learns by editing the attention maps and changing the inference results. By repeatedly editing the attention maps and making inferences so that the correct recognition results are output, the learner can acquire the grounds for the expert's judgments embedded in the ABN. The results of an evaluation experiment with subjects show that learning using the proposed method is more efficient than the conventional method.Comment: 12 pages, 5 figure

Solid-state nuclear magnetic resonance study of setting mechanism of beta-tricalcium phosphate-inositol phosphate composite cements

Solid-state nuclear magnetic resonance (NMR) spectroscopy is a technique, which can be used to provide insight into the chemical structure of non-crystalline and crystalline materials. Hence, the present study aimed to elucidate the setting mechanism of CPC, which was fabricated using beta -tricalcium phosphate (beta -TCP)-inositol phosphate (IP6) composite powder using NMR In addition, the effect of IP6 on the local chemical structure of the beta -TCP-IP6 composite powder and its hardened cement would also be investigated. The H-1 -> P-31 heteronuclear correlation NMR spectrum revealed that an amorphous hydrated layer, along with small amount of hydroxyapatite (HA) was formed on the surface of beta -TCP during the ball-milling process. Results demonstrated that the IP6 in the hydrated layer on the surface of beta -TCP inhibited the formation of HA. Moreover, the setting reaction of the cement was mainly triggered by the dissolution of the amorphous hydrated layer on beta -TCP surface, and subsequent precipitation, followed by the inter-entanglement between the HA crystals on the beta -TCP

Design and properties of polymides with electrodeposition ability for high performance insulators

Please click Additional Files below to see the full abstract

A Case of Cystic Basal Cell Carcinoma Which Shows a Homogenous Blue/Black Area under Dermatoscopy

Basal cell carcinoma (BCC) is the most common skin tumor and contains several different histopathological types. Here, we report a case of cystic basal cell carcinoma, which is relatively rare and might be clinically misdiagnosed. A dermatoscopic examination of the case revealed a homogenous blue/black area usually not seen in BCC. We reviewed 102 BCC cases resected and diagnosed at Sapporo Medical University Hospital between April 2005 and March 2010. Among them, only three were the cystic type

Musical instrument training program improves verbal memory and neural efficiency in novice older adults

楽器訓練で高齢者の認知機能が向上することを確認 --訓練による脳活動の変化を高齢者で初報告--. 京都大学プレスリリース. 2020-12-24.Previous studies indicate that musical instrument training may improve the cognitive function of older adults. However, little is known about the neural origins of training‐related improvement in cognitive function. Here, we assessed the effects of instrumental training program on cognitive functions and neural efficiency in musically naïve older adults (61–85 years old). Participants were assigned to either the intervention group, which received a 4‐month instrumental training program using keyboard harmonica, or a control group without any alternative training. Cognitive measurements and functional magnetic resonance imaging during visual working memory (VWM) task were administered before and after the intervention in both groups. Behavioral data revealed that the intervention group significantly improved memory performance on the test that measures verbal recall compared to the control group. Neuroimaging data revealed that brain activation in the right supplementary motor area, left precuneus, and bilateral posterior cingulate gyrus (PCgG) during the VWM task decreased after instrumental training only in the intervention group. Task‐related functional connectivity (FC) analysis revealed that the intervention group showed decreased FC between the right PCgG and left middle temporal gyrus, and between the left putamen and right superior temporal gyrus (lPu‐rSTG) during a VWM task after the intervention. Furthermore, a greater improvement in memory performance in the intervention group was associated with a larger reduction in lPu‐rSTG FC, which might be interpreted as improved neural efficiency. Our results indicate that the musical instrument training program may contribute to improvements in verbal memory and neural efficiency in novice older adults

SIRT1 negatively regulates the expression of Prl2C3,a senescence-associated protein

SIRT1 is a mammalian homologue of yeast longevity protein Sir2. SIRT1 deacetylates transcription factors, cofactors, and histones in an NAD+-dependent manner, and promotes cell survival, anti-oxidative function, and DNA repair. Although some studies have indicated that SIRT1 is involved in longevity, the function of SIRT1 for preventing aging and senescence is still unclear. In mouse embryonic fibroblasts (MEFs), we found that SIRT1 expression decreased by aging and IRT1 reciprocally regulated the expression level of Prl2C3, one of the prolactin-like peptides. In young MEFs, purified Prl2C3 inhibited the growth and increased the number of senescence-associated β galactosidase-positive cells with enlarged and flattened shapes. Moreover, immunostaining of human skin sections showed the expression of Prl2C3 in the basal cells of the epidermis. These results indicate that SIRT1 negatively regulates a senescence-associated protein rl2C3