データ保護システムの性能評価およびサイジング方式の研究

電気通信大学201

3D Object Discovery and Modeling Using Single RGB-D Images Containing Multiple Object Instances

Unsupervised object modeling is important in robotics, especially for handling a large set of objects. We present a method for unsupervised 3D object discovery, reconstruction, and localization that exploits multiple instances of an identical object contained in a single RGB-D image. The proposed method does not rely on segmentation, scene knowledge, or user input, and thus is easily scalable. Our method aims to find recurrent patterns in a single RGB-D image by utilizing appearance and geometry of the salient regions. We extract keypoints and match them in pairs based on their descriptors. We then generate triplets of the keypoints matching with each other using several geometric criteria to minimize false matches. The relative poses of the matched triplets are computed and clustered to discover sets of triplet pairs with similar relative poses. Triplets belonging to the same set are likely to belong to the same object and are used to construct an initial object model. Detection of remaining instances with the initial object model using RANSAC allows to further expand and refine the model. The automatically generated object models are both compact and descriptive. We show quantitative and qualitative results on RGB-D images with various objects including some from the Amazon Picking Challenge. We also demonstrate the use of our method in an object picking scenario with a robotic arm

Detecting and Grouping Identical Objects for Region Proposal and Classification

Often multiple instances of an object occur in the same scene, for example in a warehouse. Unsupervised multi-instance object discovery algorithms are able to detect and identify such objects. We use such an algorithm to provide object proposals to a convolutional neural network (CNN) based classifier. This results in fewer regions to evaluate, compared to traditional region proposal algorithms. Additionally, it enables using the joint probability of multiple instances of an object, resulting in improved classification accuracy. The proposed technique can also split a single class into multiple sub-classes corresponding to the different object types, enabling hierarchical classification.Comment: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop Deep Learning for Robotic Vision, 21 July, 2017, Honolulu, Hawai

Inhibitory Effects of Pretreatment with Radon on Acute Alcohol-Induced Hepatopathy in Mice

We previously reported that radon inhalation activates antioxidative functions in the liver and inhibits carbon tetrachloride-induced hepatopathy in mice. In addition, it has been reported that reactive oxygen species contribute to alcohol-induced hepatopathy. In this study, we examined the inhibitory effects of radon inhalation on acute alcohol- induced hepatopathy in mice. C57BL/6J mice were subjected to intraperitoneal injection of 50% alcohol (5 g/kg bodyweight) after inhaling approximately 4000 Bq/m(3) radon for 24 h. Alcohol administration significantly increased the activities of glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT) in serum, and the levels of triglyceride and lipid peroxide in the liver, suggesting acute alcohol- induced hepatopathy. Radon inhalation activated antioxidative functions in the liver. Furthermore, pretreatment with radon inhibited the depression of hepatic functions and antioxidative functions. These findings suggested that radon inhalation activated antioxidative functions in the liver and inhibited acute alcohol- induced hepatopathy in mice

Temporal sinus node modification by high-dose continuous intravenous administration of landiolol in a patient with persistent inappropriate sinus tachycardia

AbstractA 20-year-old woman underwent an electrophysiological study for drug-resistant persistent inappropriate sinus tachycardia (IST). Use of a high-dose continuous intravenous administration of landiolol, a short-acting beta-adrenoreceptor blocker, made the patient׳s heart rate suddenly drop with a slight change in the P-wave morphology. Three-dimensional right atrial (RA) activation mapping revealed that the earliest activation site moved 8mm to a lower anterior site around the high lateral RA. Radiofrequency energy applied to the earliest activation site during tachycardia was successful. A temporal sinus node modification with landiolol administration was useful for mapping and for safe catheter ablation of IST