研究者詳細 - 河口　信夫

論文 - 河口　信夫

分割表示 548 件中 161 - 180 件目／全件表示 >>

Short Segment Random Forest with Post Processing Using Label Constraint for SHL Recognition Challenge

Matsuyama Hitoshi, Urano Kenta, Hiroi Kei, Kaji Katsuhiko, Kawaguchi Nobuo

PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT) 頁： 1636-1642 2018年

回転磁石マーカに基づくスマートフォン位置推定査読有り

武島知勲, 梶克彦, 廣井慧, 河口信夫, 神山剛, 太田賢, 稲村浩

情報処理学会論文誌ジャーナル(Web) 59 巻 ( 1 ) 頁： 138 - 149 2018年

Image Translation Between Sar and Optical Imagery with Generative Adversarial Nets. 査読有り

Kenji Enomoto, Ken Sakurada, Weiming Wang, Nobuo Kawaguchi, Masashi Matsuoka, Ryosuke Nakamura

2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018, Valencia, Spain, July 22-27, 2018 2018-July 巻頁： 1752 - 1755 2018年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE

In this paper, we propose a method for the translation from Synthetic Aperture Radar (SAR) to optical images using conditional Generative Adversarial Networks (cGANs). Satellite images have been widely utilized for various purposes, such as natural environment monitoring (pollution, forest or rivers), transportation improvement and prompt emergency response to disasters. However, the obscurity caused by clouds leads to unstable monitoring of the ground situation while using the optical camera. Images captured by a longer wavelength are introduced to reduce the effects of clouds. In particular, SAR images are known to be nearly unaffected by clouds and are often used for stably observing the ground situation. On the other hand, SAR images have lower spatial resolution and visibility than optical images. Therefore, we propose a deep neural network that generates optical images from SAR images. Finally, we confirm the feasibility of the proposed network on a dataset consisting of optical images and the corresponding SAR images.

DOI： 10.1109/IGARSS.2018.8518719

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Scale Estimation of Monocular SfM for a Multi-modal Stereo Camera. 査読有り

Shinya Sumikura, Ken Sakurada, Nobuo Kawaguchi, Ryosuke Nakamura

CoRR abs/1810.11856 巻 2018年

仮想空間を利用した空間認識能力の計測手法の提案査読有り

嶋田光佑, 廣井慧, 梶克彦, 河口信夫

情報処理学会論文誌 59 巻 ( 1 ) 頁： 150 - 167 2018年

Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard

Wang Weimin, Sakurada Ken, Kawaguchi Nobuo

REMOTE SENSING 9 巻 ( 8 ) 2017年8月

FloodEye: Real-time flash flood prediction system for urban complex water flow

Hiroi K., Kawaguchi N.

Proceedings of IEEE Sensors 2017年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：Proceedings of IEEE Sensors

This study presents a water-level sensor system that has multiple functions: real-time river-level monitoring and high accurate flood prediction for urban complex water flow (CWF) flooding caused by Localized Heavy Rain. Traditional water-level sensors for large-scale river can detect water-level rising, though they have limitations in detecting urban river dyke height to alert about flooding. This is a result of various riverside environmental limitations. Additionally, previous prediction methods are difficult to detect CWF flooding with high accuracy because water rising differ depends on a location's environment. Therefore, we propose a detection scheme for CWF by developing a water-level sensor system that works in various installation environments using infrared image processing with both low installation and operation cost. We implemented a CWF prediction system that produces accurate and early predictions using a Linear Regression (LR) of deep learning approach with data assimilation. Evaluating based on actual installations (over 1,000 days, 13 locations), our system proved to accurately monitor and predict water-level rising after 5 minutes.

DOI： 10.1109/ICSENS.2016.7808626

Scopus

Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets

Enomoto Kenji, Sakurada Ken, Wang Weimin, Fukui Hiroshi, Matsuoka Masashi, Nakamura Ryosuke, Kawaguchi Nobuo

2017 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW) 頁： 1533-1541 2017年

5th Int. Workshop on Human Activity Sensing Corpus and Applications (HASCA): Towards Open-Ended Context Awareness

Kawaguchi Nobuo, Inoue Sozo, Nishio Nobuhiko, Pirttikangas Susanna, Roggen Daniel, Van Laerhoven Kristof

PROCEEDINGS OF THE 2017 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2017 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC '17 ADJUNCT) 頁： 530-536 2017年

A Location Estimation Method using Mobile BLE Tags with Tandem Scanners

Urano Kenta, Hiroi Kei, Kaji Katsuhiko, Kawaguchi Nobuo

Compensation Scheme for PDR using Sparse Location and Error Model

Nozaki Junto, Hiroi Kei, Kaji Katsuhiko, Kawaguchi Nobuo

Event.Locky: System of event-data extraction from webpages based onweb mining 査読有り

Liao C., Hiroi K., Kaji K., Sakurada K., Kawaguchi N.

Journal of Information Processing 25 巻 ( 0 ) 頁： 321 - 330 2017年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Journal of Information Processing

Nearby event data, such as those for exhibitions and sales promotions, may help users spend their free time more efficiently. However, most event data are hidden in millions of webpages, which is very time-consuming for a user to find such data. To address this issue, we use web mining that extracts event data from webpages. In this paper, we propose and discuss the implementation of Event.Locky – a system for extracting event data from webpages in a user-defined area and displaying them to a user in a spatial-temporal structure. Furthermore, we design two core algorithms for event data extraction in Event.Locky: webpage-data-record extraction and event-record classification. The former is used to convert a semi-structural HTML document into processable structured data. The latter filters out non-event data from extracted data records using machine learning. We trained and evaluated Event.Locky with an actual dataset composed by 96 restaurants and shops at Nagoya train station. As a result, our event-classification algorithm achieved an F1 score of 91.61%, an increase of 3.07% from current event-classification algorithms. The combination of our event-classification algorithm and our data-record-extraction algorithm achieved F1 score 83.96% to extract event records from webpages. That increased 1.6% from current algorithm. Finally, we discuss the feasibility of Event.Locky in an actual online environment through the implementation of a demonstration application.

DOI： 10.2197/ipsjjip.25.321

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通路に設置した回転する磁石による歩行者の通過検出手法査読有り

武島知勲, 梶克彦, 廣井慧, 河口信夫, 神山剛, 太田賢, 稲村浩

情報処理学会論文誌 58 巻 ( 1 ) 頁： 43 - 56 2017年

歩行時の磁気センシングデータを利用した屋内位置推定手法査読有り

村田雄哉, 梶克彦, 廣井慧, 河口信夫, 神山剛, 太田賢, 稲村浩

情報処理学会論文誌ジャーナル(Web) 58 巻 ( 1 ) 頁： 57 - 67 2017年

A three-dimensional smartphone positioning method using a spinning magnet marker 査読有り

Watanabe K., Hiroi K., Kamiyama T., Sano H., Tsukamoto M., Katagiri M., Ikeda D., Kaji K., Kawaguchi N.

2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017 2018-January 巻頁： 1 - 7 2017年

記述言語：日本語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2017 10th International Conference on Mobile Computing and Ubiquitous Network, ICMU 2017

We propose a method of detecting the precise three-dimensional position of a smartphone using a Spinning Magnet Marker (SMM). An SMM is a device that generates a dynamic magnetic field by spinning a strong magnet with a motor. In the proposed method, the magnetic sensor of a smartphone detects the magnetic field generated by an SMM, and the three-imensional position of the smartphone is estimated with an accuracy of better than several tens of centimeters based on the magnetic field and the motor angle of the SMM. It is expected that such precise three-dimensional positioning will enable not only better navigation of users to their destinations but also a better understanding of human behavior. First, we construct theoretical equations relating the magnetic field generated by the SMM to the three-dimensional position of the smartphone in three-dimensional polar coordinates. Second, we evaluate the estimation accuracy of the proposed method with the distance between the SMM and the smartphone fixed at 1.0 m. The azimuth is estimated with a mean error of within 11 degrees, and the elevation is estimated with a mean error of within 10 degrees. The distance is estimated with a mean error of within 19 cm at distances of up to 3.0 m.

DOI： 10.23919/ICMU.2017.8330076

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Dense Optical Flow based Change Detection Network Robust to Difference of Camera Viewpoints. 査読有り

Ken Sakurada, Weimin Wang, Nobuo Kawaguchi, Ryosuke Nakamura

CoRR abs/1712.02941 巻 2017年

A Three-Dimensional Smartphone Positioning Method using a Spinning Magnet Marker

Watanabe Kosuke, Hiroi Kei, Kamiyama Takeshi, Sano Hiroyuki, Tsukamoto Masakatsu, Katagiri Masaji, Ikeda Daizo, Kaji Katsuhiko, Kawaguchi Nobuo

2017 TENTH INTERNATIONAL CONFERENCE ON MOBILE COMPUTING AND UBIQUITOUS NETWORK (ICMU) 頁： 38 - 44 2017年

「究極のヒューマンインタフェースの実現を目指して」

河口信夫

知能と情報 28 巻 ( 6 ) 頁： 169 - 169 2016年12月

Wi-Fi Human Behavior Analysis and BLE Tag Localization: A Case Study at an Underground Shopping Mall 査読有り

Kawaguchi N., Hiroi K., Shionozaki A., Asukai M., Nasu T., Hashimoto Y., Nakamura T., Gotou T., Ando S.

ACM International Conference Proceeding Series 28- 巻頁： 151 - 159 2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：ACM International Conference Proceeding Series

Techniques for obtaining customers' behavior (dwell time, count, and flow) in a shopping mall or large exhibit are highly sought-after by organizers or shop owners. Additionally, ways of effectively directing customers from cyber space such as the Web or smartphone apps to physical retail stores are also in high demand. "Online to Offline (O2O) Marketing" has recently been attracting attention to make these a reality. However, the know-how accumulated through "O2O Marketing" is not shared widely as it can be sensitive for business and customer's privacy. In this paper, we provide the knowledge obtained through the demonstration experiments held by the "O2O Digital Marketing Study Group" organized by NPO Lisra at a large underground shopping mall in Nagoya. 250 BLE tags and 12 Wi-Fi scanners were installed in this mall. We also organized a "coupon campaign" to increase the number of participants. We were able to effectively collect visiting customer count measurements via Wi-Fi scanners irrespective of the anonymization of BSSID, as our results showed similar trends collected by optical human detectors inherently installed at the venue. This paper provides preliminary insight into understanding the behaviors of retail shoppers and we believe this is a firm starting point for this area.

DOI： 10.1145/2994374.2994403

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PIEM: Path Independent Evaluation Metric for Relative Localization 査読有り

Abe M., Kaji K., Hiroi K., Kawaguchi N.

2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016 頁： 1 - 8 2016年11月

記述言語：英語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2016 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2016

There are many methods for indoor positioning. These methods are divided into the relative localization and absolute localization. In the relative localization, one widely used method is Pedestrian Dead Reckoning (PDR). Relative localization estimates the moving distance, orientation, and height of the pedestrian. However, relative localization has a problem caused by an accumulated error: the longer the path, the worse the accuracy of relative localization. There is another problem in the existing evaluating metrics: they compare only the actual location and the estimated location of the destination. Relative localization also has this evaluation problem. We propose PIEM: Path Independent Evaluation Metric for Relative Localization. PIEM is a path independent evaluation metric, considering the complexity of the path; distance, orientation, and height. Then we evaluate these three factors of relative localization in addition to the position. Our proposed method showed more consistent results for the complexity of the path than the existing methods of relative localization evaluation.

DOI： 10.1109/IPIN.2016.7743587

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