Last update: 09 Mar., 2018


    International Journal

    1. 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.
    2. 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. (Original version is a domestic journal)
    3. 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.(Original version is a domestic journal)
    4. 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. DOI: 10.20965/jrm.2015.p0174

    International Conference

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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. 
    6. 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. 
    7. 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.
    8. 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.
    9. 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.
    10. 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)
    11. 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)
    12. 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.
    13. 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.
    14. 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)
    15. 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.
    16. 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.
    17. 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)
    18. Shuichi Akizuki，Manabu Hashimoto, Fast and Reliable 3-D Object Recognition based on Surface Normal Distributions，International Symposium on Optomechatronic Technologies, Oct. 2013.(oral)
    19. 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.
    20. 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)
    21. 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)

    Awards

    1. Amazon Robotics Challenge 2017 Stow Task - 3rd Place,  (as a member of Team MC^2), 2017/07/30. 
    2. Amazon Picking Challenge 2015, "Travel Reimbursement Awards", as a member of Team C^2M, 2015/3/26.