HANDS18: Methods, Techniques and Applications for Hand Observation

This report outlines the proceedings of the Fourth International Workshop on Observing and Understanding Hands in Action (HANDS 2018). The fourth instantiation of this workshop attracted significant interest from both academia and the industry. The program of the workshop included regular papers that are published as the workshop’s proceedings, extended abstracts, invited posters, and invited talks. Topics of the submitted works and invited talks and posters included novel methods for hand pose estimation from RGB, depth, or skeletal data, datasets for special cases and real-world applications, and techniques for hand motion re-targeting and hand gesture recognition. The invited speakers are leaders in their respective areas of specialization, coming from both industry and academia. The main conclusions that can be drawn are the turn of the community towards RGB data and the maturation of some methods and techniques, which in turn has led to increasing interest for real-world applications.

[1]  Ken Perlin,et al.  Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks , 2014, ACM Trans. Graph..

[2]  Jianfei Cai,et al.  Weakly-Supervised 3D Hand Pose Estimation from Monocular RGB Images , 2018, ECCV.

[3]  Andrew W. Fitzgibbon,et al.  Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences , 2016, ACM Trans. Graph..

[4]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[5]  Christian Theobalt,et al.  GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[6]  Antti Oulasvirta,et al.  Real-Time Joint Tracking of a Hand Manipulating an Object from RGB-D Input , 2016, ECCV.

[7]  Hans-Peter Seidel,et al.  Real-Time Hand Tracking Using a Sum of Anisotropic Gaussians Model , 2014, 2014 2nd International Conference on 3D Vision.

[8]  Huazhong Yang,et al.  Spatial-Temporal Attention Res-TCN for Skeleton-Based Dynamic Hand Gesture Recognition , 2018, ECCV Workshops.

[9]  Sergio Escalera,et al.  Depth-Based 3D Hand Pose Estimation: From Current Achievements to Future Goals , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[10]  Michael J. Black,et al.  ClothCap , 2017, ACM Trans. Graph..

[11]  Hazem Wannous,et al.  Skeleton-Based Dynamic Hand Gesture Recognition , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[12]  Christian Theobalt,et al.  Real-Time Hand Tracking Under Occlusion from an Egocentric RGB-D Sensor , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[13]  Junsong Yuan,et al.  Point-to-Point Regression PointNet for 3D Hand Pose Estimation , 2018, ECCV.

[14]  David Filliat,et al.  3D Hand Gesture Recognition Using a Depth and Skeletal Dataset , 2017, 3DOR@Eurographics.

[15]  Bernt Schiele,et al.  Pictorial structures revisited: People detection and articulated pose estimation , 2009, CVPR.

[16]  Oliver Deussen,et al.  Estimating 2D Multi-hand Poses from Single Depth Images , 2018, ECCV Workshops.

[17]  Antonis A. Argyros,et al.  Joint 3D Tracking of a Deformable Object in Interaction with a Hand , 2018, ECCV.

[18]  Antti Oulasvirta,et al.  Interactive Markerless Articulated Hand Motion Tracking Using RGB and Depth Data , 2013, 2013 IEEE International Conference on Computer Vision.

[19]  Zhen He,et al.  Numerical Coordinate Regression with Convolutional Neural Networks , 2018, ArXiv.

[20]  Cristóbal Curio,et al.  Adapting Egocentric Visual Hand Pose Estimation Towards a Robot-Controlled Exoskeleton , 2018, ECCV Workshops.

[21]  Andrea Tagliasacchi,et al.  Sphere-meshes for real-time hand modeling and tracking , 2016, ACM Trans. Graph..

[22]  Lovekesh Vig,et al.  DrawInAir: A Lightweight Gestural Interface Based on Fingertip Regression , 2018, ECCV Workshops.

[23]  Qi Ye,et al.  Occlusion-aware Hand Pose Estimation Using Hierarchical Mixture Density Network , 2017, ECCV.

[24]  Paulina J. M. Bank,et al.  Hand-tremor frequency estimation in videos , 2018, ECCV Workshops.

[25]  J. Schmidhuber,et al.  Framewise phoneme classification with bidirectional LSTM networks , 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

[26]  Kenrick Kin,et al.  Online optical marker-based hand tracking with deep labels , 2018, ACM Trans. Graph..

[27]  Steve Marschner,et al.  Matching Real Fabrics with Micro-Appearance Models , 2015, ACM Trans. Graph..

[28]  Tamim Asfour,et al.  The KIT whole-body human motion database , 2015, 2015 International Conference on Advanced Robotics (ICAR).

[29]  拓海 杉山,et al.  “Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告 , 2017 .

[30]  Yong-Liang Yang,et al.  HandMap: Robust Hand Pose Estimation via Intermediate Dense Guidance Map Supervision , 2018, ECCV.

[31]  Gang Yu,et al.  Cascaded Pyramid Network for Multi-person Pose Estimation , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[32]  Varun Ramakrishna,et al.  Convolutional Pose Machines , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Guillermo Garcia-Hernando,et al.  Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation , 2018, ECCV Workshops.

[34]  Pavlo Molchanov,et al.  Hand Pose Estimation via Latent 2.5D Heatmap Regression , 2018, ECCV.

[35]  Tien-Tsin Wong,et al.  Deep unsupervised pixelization , 2018, ACM Trans. Graph..

[36]  Andrew W. Fitzgibbon,et al.  Online generative model personalization for hand tracking , 2017, ACM Trans. Graph..

[37]  Kaiming He,et al.  Mask R-CNN , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[38]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[39]  Andrea Tagliasacchi,et al.  Robust Articulated-ICP for Real-Time Hand Tracking , 2015 .

[40]  Dongheui Lee,et al.  Model-based Hand Pose Estimation for Generalized Hand Shape with Spatial Transformer Network , 2018, ECCV 2018.

[41]  Yichen Wei,et al.  Model-Based Deep Hand Pose Estimation , 2016, IJCAI.