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PhD (Curriculum Vitae) Phone: (+81)22-374-3627 Advisor: Prof. Takayuki Okatani |
Employment
- Postdoctoral Researcher, Tokyo Institute of Technology (April 2015 - present)
- Advisor: Masatoshi Okutomi
- Research Assistant, Tohoku University (April 2014 - March 2015)
- JSPS Research Fellow (DC2), Tohoku University (April 2012 - March 2014)
- Research Assistant, Tohoku University (April 2011 - March 2012)
Education
- Visiting Scholar, The Robotics Institute, Carnegie Mellon University (April 2013 - March 2014)
- Advisor: Kris M. Kitani, Yaser Ajmal Sheikh, Takeo Kanade
- PhD, Information Science, Tohoku University (April 2011 - March 2015)
- Advisor: Takayuki Okatani, Koichiro Deguchi
- MS, Information Science, Tohoku University (April 2019 - March 2011)
- Advisor: Satoshi Tadokoro
- BS, Mechanical Engineering, Tohoku University (April 2005 - March 2009)
Research
Massive City-scale Surface Condition Analysis using Ground and Aerial Imagery
Automated visual analysis is an effective method for understanding changes in natural phenomena over massive city-scale landscapes. However, the viewpoint spectrum across which image data can be acquired is extremely wide, ranging from macro-level overhead (aerial) images spanning several kilometers to micro-level front-parallel (street-view) images that might only span a few meters. This work presents a unified framework for robustly integrating image data taken at vastly different viewpoints to generate large-scale estimates of land surface conditions. To validate our approach we attempt to estimate the amount of post-Tsunami damage over the entire city of Kamaishi, Japan (over 4 million square-meters). Our results show that our approach can efficiently integrate both micro and macro-level images, along with other forms of meta-data, to efficiently estimate city-scale phenomena. We evaluate our approach on two modes of land condition analysis, namely, city-scale debris and greenery estimation, to show the ability of our method to generalize to a diverse set of estimation tasks.
Ken Sakurada, Takayuki Okatani and Kris M. Kitani, “Massive City-scale Surface Condition Analysis using Ground and Aerial Imagery”, ACCV2014 (Oral, Acceptance Rate: Less than 4%), "Best Application Paper Honorable Mention Award" [paper]
Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-mounted Camera
This paper proposes a method for detecting temporal changes of the three-dimensional structure of an outdoor scene from its multi-view images captured at two separate times. For the images, we consider those captured by a camera mounted on a vehicle running in a city street. The method estimates scene structures probabilistically, not deterministically, and based on their estimates, it evaluates the probability of structural changes in the scene, where the inputs are the similarity of the local image patches among the multi-view images. The aim of the probabilistic treatment is to maximize the accuracy of change detection, behind which there is our conjecture that although it is dicult to estimate the scene structures deterministically, it should be easier to detect their changes. The proposed method is compared with the methods that use multi-view stereo (MVS) to reconstruct the scene structures of the two time points and then di fferentiate them to detect changes. The experimental results show that the proposed method outperforms such MVS-based methods.
Ken Sakurada, Takayuki Okatani and Koichiro Deguchi, "Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-mounted Camera" , CVPR 2013 (Poster, Acceptance Rate:25.2%) ([paper], [supplementary material], [poster], [project])
Publication
- Ken Sakurada, Takayuki Okatani, “Change Detection from a Street Image Pair using CNN Features and Superpixel Segmentation”, BMVC2015 (Poster, Acceptance Rate: 33%) [paper]
- Ken Sakurada, Takayuki Okatani, Kris M. Kitani, “Massive City-scale Surface Condition Analysis using Ground and Aerial Imagery”, ACCV2014 (Oral, Acceptance Rate: Less than 4%), "Best Application Paper Honorable Mention Award" [paper]
- Ken Sakurada, Takayuki Okatani, Koichiro Deguchi, “Detecting Changes in 3D Structure of a Scene from Multi-view Images Captured by a Vehicle-mounted Camera”, CVPR2013 (Poster, Acceptance Rate: 25.2%) [paper], [supplementary material], [poster], [project]
- Takayuki Okatani, Ken Sakurada, Jun Yanagisawa, Daiki Tetsuka, Koichiro Deguchi, “Creating Multi-Viewpoint Panoramas of Streets with Sparsely Located Buildings”, FSR2012
- Ken Sakurada, Eijiro Takeuchi, Kazunori Ohno, Satoshi Tadokoro, “Development of Motion Model and Position Correction Method using Terrain Information for Tracked Vehicles with Sub-Crawlers”, IROS2010
- Ken Sakurada, Shihiko. Suzuki, Kazunori. Ohno, Eeijiro. Takeuchi, Satoshi Tadokoro, Akihiko Hata, Naoki Miyahara, Kazuyuki Higashi, “Real-time Prediction of Fall and Collision of Tracked Vehicle for Remote-Control Support”, SII2010, "Best Paper Award Finalist"
- Akihiko Hata, Kazunori Ohno, Eijiro Takeuchi, Satoshi Tadokoro, Ken Sakurada, Naoki Miyahara, Kazuyuki Higashi, “Development of a Laser Scan Method to Decrease Hidden Areas Caused by Objects Like Pole at Whole 3-D Shape Measurement”, SII2010
HONORS AND AWARDS
- MIRU2015 Frontier Award
- ACCV2014 Best Application Paper Honorable Mention Award
- SII2010 Best Paper Award Finalist
- Graduation Honor, Mechanical Major in Graduate School of Information Science, Tohoku University, 2010
- Second Place of Rescue Robot League of RoboCup World 2009 （Team: Pelican United）
- Eiji Muto Student Award, Japan Society for Design Engineering, 2008