Natsuki Yamanobe,
Weiwei Wan, Ixchel G. Ramirez-Alpizar, Damien Petit, Tokuo Tsuji, Shuichi Akizuki, Manabu Hashimoto, Kazuyuki Nagata, Kensuke
Harada, A Brief Review of Affordance in Robotic Manipulation Research, Journal of Advanced Robotics, Vol. 31, Issue 19-20, pp. 1086-1101, 2017.
[paper]
武井翔一, 秋月秀一, 橋本学,
マルチスケールシェル領域の点群占有率に基づく3次元特徴量の提案,電気学会論文誌C, Vol. 136, No. 8, pp.1078-1084, 2016. [paper] English ver.: Shoichi Takei, Shuichi Akizuki, Manabu Hashimoto, A Proposal of 3D Feature Based on Occupancy of Point Cloud in
Multiscale Shell Region, Electronics and Communications in Japan, Vol.XX, No.X, 2017.
橋本学, 秋月秀一, 武井翔一, 物体認識のための3 次元特徴量の研究動向,電気学会論文誌C, Vol. 136, No. 8,
pp.1038-1046, 2016. [paper] English ver.: Manabu Hashimoto, Shuichi Akizuki,
Shoichi Takei, A Survey and Technology Trends of 3D Features for Object Recognition, Electronics and Communications in Japan, Vol.100, Issue 11, pp. 31-42, 2017.
Shuichi Akizuki, Manabu Hashimoto, Stable Position and Pose Estimation of Industrial Parts using Evaluation of
Observability of 3D Vector Pairs, Journal of Robotics and Mechatronics (Special Issue on Vision and Motion Control), Vol.27, No.2, pp.174-181, 2015. [paper] DOI: 10.20965/jrm.2015.p0174
International Conference on Machine Vision Applications (MVA), 2019/05/30.
Shuichi
Akizukiand Manabu Hashimoto, Semi-automatic training data generation for semantic
segmentation using 6DoF pose estimation, 14th International Conference on Computer Vision Theory and Applications (VISAPP), Prague, Czech Republic,
2019. (oral) [pdf]
Teppei Suzuki, Shuichi Akizuki, Naoki Kato and Yoshimitsu Aoki, Superpixel Convolution for Segmentation, 25th IEEE International Conference on Image Processing (ICIP),
2018.
Shuichi
Akizukiand Yoshimitsu Aoki, Tactile Logging for Understanding Plausible Tool Use
Based on Human Demonstration, 1st International Workshop on Vision for Interaction and Behaviour undErstanding (VIBE) (Workshop of BMVC2018), Newcastle upon Tyne, UK,
2018/9/6. (oral) [pdf]
Shuichi Akizuki and Yoshimitsu Aoki, Pose Alignment for Different Objects using Affordance
Cues, International Workshop on Advanced Image Technology 2018 (IWAIT2018), pp.1-3, Chiang Mai, Thailand, 2018/01/08.
Shuichi Akizuki, Masaki Iizuka, Kentaro Kozai and Manabu Hashimoto, Functional Attribute Estimation using Local
Evidence and Semi-global Surface Structure, 3rd International Workshop on Recovering 6D Object Pose (Workshop of ICCV2017), Venice, Italy, 2017/10/29.
Shuichi Akizuki, Masaki Iizuka, Kentaro Kozai and Manabu
Hashimoto, Functional Attribute Estimation using Local Evidences and Semi-global Surface Structure, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),
p.3174, Vancouver, BC, Canada, 2017/9/26.
H. Fujiyoshi, T. Yamashita, Y. Yamauchi, T. Hasegawa, M. Hashimoto, S. Akizuki,
Y. Domae and R. Kawanishi, Team C^2M: Two Cooperative Robots for Picking and Stowing in Amazon Picking Challenge 2016, Warehouse Picking Automation Workshop on International Conference on
Robotics and Automation, 2017.
Masaki Iizuka, Shuichi Akizuki, Manabu Hashimoto,
Affordance-based 3D Feature for Generic Object Recognition, Proceedings of 13th International Conference on Quality Control by Artificial Vision (QCAV), Vol.10338, 103380W-1-6, DOI:
10.1117/12.2266917, Tokyo, Japan, 2017/5/15.
Shuichi Akizuki, Haruki Aruga, Manabu Hashimoto, Hand Pose Estimation using Global Shape and
Hand Parts Consistency, International Workshop on Advanced Image Technology (IWAIT), pp. 1-4, Jan. 2017.
Shuichi Akizuki and Manabu Hashimoto, Physical Reasoning for 3D Object Recognition using Global Hypothesis Verification, European Conference on Computer Vision Workshops (2nd International Workshop on Recovering 6D Object
Pose), LNCS Computer Vision – ECCV 2016 Workshops, Part III, Vol. 9915, pp. 595-605, Oct. 9, 2016.
Shuichi Akizuki, Masaki Iizuka and
Manabu Hashimoto, “Affordance”-focused Features for Generic Object Recognition, European Conference on Computer Vision Workshops (2nd International Workshop on Recovering 6D Object Pose),
2016.
K.Tobitani, S.Akizuki, K.Katahira, M.Hashimoto, N.Nagata, A Comparison Study on 3D Features in Term of Effective Representation for
Impression of Shape. The 2nd International Conference on DigitalFabrication (ICDF), No.22, 2016.
Shuichi Akizuki, Manabu Hashimoto, Multiple 3D Object Recognition using RGB-D Data and Physical Consistency for Automated Warehousing
Robots, 11th International Conference on Computer Vision Theory and Applications (VISAPP), pp. 605-609, 2016.(oral)
Shuichi Akizuki, Manabu Hashimoto, Relative Point Density (RPD) Feature for Object Recognition Independent of Point Cloud Sparseness,The
Korea-Japan joint workshop on Frontiers of Computer Vision (FCV) , pp.137-140, 2016.(oral)
Shoichi Takei, Shuichi Akizuki, Manabu Hashimoto, SHORT: A Fast 3D Feature Description based on Estimating Occupancy in Spherical
Shell Regions, Proceedings of the 30th International Conference on Image and Vision Computing New Zealand, Auckland, New Zealand, 2015/11/24.
Shuichi Akizuki, Manabu Hashimoto, DPN-LRF: A Local Reference Frame for Robustly Handling Density Differences and Partial Occlusions,11th
International Symposium on Visual Computing (ISVC), Part I, LNCS 9474, pp.878-887, 2015.
Shuichi Akizuki, Manabu Hashimoto, A Proposal of the Global Reference Frame for Surface Flatness-independent 3D Object Detection,Proc.
Joint Conference of the International Workshop on Advanced Image Technology(IWAIT) and the International Forum on Medical Imaging in Asia(IFMIA),OS. 27, 2015.(oral)
Masanobu Nagase,Shuichi Akizuki,Manabu Hashimoto, High-speed and Reliable Object Recognition based on Low-dimensional Local Shape
Features,Proc. the 13th International Conference on Control, Automation, Robotics and Vision(ICARCV),pp.82-87,2014.
Shoichi Takei,Shuichi Akizuki,Manabu Hashimoto,3D Object Recognition using Effective Features Selected by Evaluating Performance of
Discrimination,Proc. the 13th International Conference on Control, Automation, Robotics and Vision(ICARCV),pp.70-75,2014.
Shuichi Akizuki, Manabu Hashimoto, Position and Pose Recognition of Randomly Stacked Objects using Highly
Observable 3D Vector Pairs,Proc. the 40th Annual Conference of the IEEE Industrial Electronics Society,pp.5266-5271,Oct. 2014.(oral)
Shuichi Akizuki,Manabu Hashimoto, Fast and Reliable 3-D Object Recognition based on Surface Normal Distributions,International Symposium
on Optomechatronic Technologies, Oct. 2013.(oral)
Masanobu Nagase,Shuichi Akizuki,Manabu Hashimoto, 3-D Feature Point Matching for Object Recognition Based on Estimation of Local Shape
Distinctiveness,15th International Conference on Computer Analysis of Images and Patterns, Part I, LNCS,Vol.8047, pp.473-481, Aug. 2013.
Shuichi Akizuki, Manabu Hashimoto, Robust Matching for Low-texture Images based on Co-occurrence of Geometry-optimized Pixel Patterns,
IEEE Proc. International Conference on Quality Control by Artificial Vision, pp.113-116, May 2013.(oral)
Shuichi Akizuki, Manabu Hashimoto, High-speed and Reliable Object Recognition using Distinctive 3-D Vector Pairs in a Range Image,IEEE
Proc. International Symposium on Optomechatronic Technologies,pp.1-6, Oct. 2012.(oral)
Shuichi Akizuki, Manabu Hashimoto,Multiple 3D Object Recognition Using
Shape Consistency and Physical Possibility,第19回画像の認識・理解シンポジウム(MIRU),2016/8/4.(Oral) MIRU学生奨励賞