Skip to main content
SpringerLink
Log in

A Survey of Hand Posture Estimation Techniques and Optimisation Algorithms

  • Chapter
  • First Online:
Optimisation Algorithms for Hand Posture Estimation

Part of the book series: Algorithms for Intelligent Systems ((AIS))

  • 355 Accesses

Abstract

This chapter reviews a wide range of relevant works in the literature of two fields: hand posture estimation and evolutionary stochastic optimisation. Since this book contributes to the field of hand posture estimation, this chapter analyses the literature of hand posture estimation and highlights the gaps as well. The logical order of sections is illustrated in Fig. 2.1.

Part of this chapter has been reprinted from Shahrzad Saremi, Seyedali Mirjalili, Andrew Lewis, Alan Wee Chung Liew, Jin Song Dong: Enhanced multi-objective particle swarm optimisation for estimating hand postures, Knowledge-Based Systems, Volume 158, pp. 175–195, 2018 with permission from Elsevier.

Part of this chapter has been reprinted from Shahrzad Saremi, Seyedali Mirjalili, Andrew Lewis: Vision-based hand posture estimation using a new hand model made of simple components, Optik, Volume 167, pp. 15–24, 2018 with permission from Elsevier.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kevin NYY, Ranganath S, Ghosh D (2004) Trajectory modeling in gesture recognition using cybergloves/sup/spl reg//and magnetic trackers. In: 2004 IEEE region 10 conference TENCON 2004. IEEE, pp 571–574

    Google Scholar 

  2. Malik S, Laszlo J (2004) Visual touchpad: a two-handed gestural input device. In: Proceedings of the 6th international conference on multimodal interfaces. ACM, pp 289–296

    Google Scholar 

  3. Wilson AD (2004) Touchlight: an imaging touch screen and display for gesture-based interaction. In: Proceedings of the 6th international conference on Multimodal interfaces. ACM, pp 69–76

    Google Scholar 

  4. Li Y (2012) Hand gesture recognition using kinect. In 2012 IEEE 3rd International conference on software engineering and service science (ICSESS). IEEE, pp 196–199

    Google Scholar 

  5. Ren Z, Yuan J, Meng J, Zhang Z (2013) Robust part-based hand gesture recognition using kinect sensor. IEEE Trans Multimed 15(5):1110–1120

    Article  Google Scholar 

  6. Coogan T, Awad G, Han J, Sutherland A (2006) Real time hand gesture recognition including hand segmentation and tracking. In: International symposium on visual computing. Springer, pp 495–504

    Google Scholar 

  7. Singhai S, Satsangi C (2014) Hand segmentation for hand gesture recognition. In: Workshop on interactive multimedia on mobile & portable devices, vol 1, pp 48–52

    Google Scholar 

  8. Lee J, Kunii TL (1995) Model-based analysis of hand posture. IEEE Comput Graph Appl 15(5):77–86

    Google Scholar 

  9. Bourke AK, Obrien JV, Lyons GM (2007) Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm. Gait & Posture 26(2):194–199

    Article  Google Scholar 

  10. Erol A, Bebis G, Nicolescu M, Boyle RD, Twombly, X (2007) Vision-based hand pose estimation: a review. Comput Vis Image Underst 108(1):52–73

    Article  Google Scholar 

  11. Barsoum E (2016) Articulated hand pose estimation review. arXiv:1604.06195

  12. Darrell T J, Essa IA, Pentland AP (1996) Task-specific gesture analysis in real-time using interpolated views. IEEE Trans Pattern Anal Mach Intell 18(12):1236–1242

    Article  Google Scholar 

  13. Isard M, Blake A (1998) Condensationconditional density propagation for visual tracking. Int J Comput Vis 29(1):5–28

    Article  Google Scholar 

  14. Argyros AA, Lourakis MI (2006) Binocular hand tracking and reconstruction based on 2d shape matching. In: 2006 18th international conference on pattern recognition ICPR, vol 1, pp 207–210. IEEE

    Google Scholar 

  15. Taylor J, Bordeaux L, Cashman T, Corish B, Keskin C, Sharp T, Soto E, Sweeney D, Valentin J, Luff B, et al (2016) Efficient and precise interactive hand tracking through joint, continuous optimization of pose and correspondences. ACM Trans Graph (TOG) 35(4):143

    Article  Google Scholar 

  16. Rehg JM, Kanade T (1994) Visual tracking of high dof articulated structures: an application to human hand tracking. In: European conference on computer vision. Springer, pp 35–46

    Google Scholar 

  17. Heap T, Hogg D (1996) Towards 3d hand tracking using a deformable model. In: Proceedings of the second international conference on automatic face and gesture recognition. IEEE, pp 140–145

    Google Scholar 

  18. Pham A (2009) E3: Microsoft shows off gesture control technology for xbox 360. Los Angeles Times, 1

    Google Scholar 

  19. Shotton J, Sharp T, Kipman A, Fitzgibbon A, Finocchio M, Blake A, Cook M, Moore R (2013) Real-time human pose recognition in parts from single depth images. Commun ACM 56(1):116–124

    Article  Google Scholar 

  20. Coscia P, Palmieri FA, Castaldo F, Cavallo A (2016) 3-d hand pose estimation from kinects point cloud using appearance matching. In: Advances in neural networks. Springer, pp 37–45

    Google Scholar 

  21. Ballan L, Taneja A, Gall J, Van Gool L, Pollefeys M (2012) Motion capture of hands in action using discriminative salient points. In: European conference on computer vision. Springer, pp 640–653

    Google Scholar 

  22. de La Gorce M, Fleet DJ, Paragios N (2011) Model-based 3d hand pose estimation from monocular video. IEEE Trans Pattern Anal Mach Intell, 33(9):1793–1805, 2011

    Google Scholar 

  23. Oikonomidis I, Kyriazis N, Argyros AA (2011) Efficient model-based 3d tracking of hand articulations using kinect. In: BMVC, vol 1, p 3

    Google Scholar 

  24. Shi Y et al (2001) Particle swarm optimization: developments, applications and resources. In: Proceedings of the 2001 Congress on evolutionary computation, vol 1. IEEE, pp 81–86

    Google Scholar 

  25. Qian C, Sun X, Wei Y, Tang X, Sun J (2014) Realtime and robust hand tracking from depth. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1106–1113

    Google Scholar 

  26. Tkach A, Pauly M, Tagliasacchi A (2016) Sphere-meshes for real-time hand modeling and tracking. ACM Trans Graph (TOG) 35(6):222

    Article  Google Scholar 

  27. Tagliasacchi A, Schröder M, Tkach A, Bouaziz S, Botsch M, Pauly, M (2015) Robust articulated-icp for real-time hand tracking. In computer graphics forum, vol 34. Wiley Online Library, pp 101–114

    Google Scholar 

  28. Holub AD, Welling M, Perona P (2008) Hybrid generative-discriminative visual categorization. Int J Comput Vis 77(1):239–258

    Article  Google Scholar 

  29. Sharp T, Keskin C, Robertson D, Taylor J, Shotton J, Kim D, Rhemann C, Leichter I, Vinnikov A, Wei Y et al (2015) Accurate, robust, and flexible real-time hand tracking. In: Proceedings of the 33rd Annual ACM conference on human factors in computing systems. ACM, pp 3633–3642

    Google Scholar 

  30. Krejov P, Gilbert A, Bowden R (2015) Combining discriminative and model based approaches for hand pose estimation. In: 2015 11th IEEE international conference and workshops on automatic face and gesture recognition (FG), vol 1. IEEE, pp 1–7

    Google Scholar 

  31. Sridhar S, Mueller F, Oulasvirta A, Theobalt C (2015) Fast and robust hand tracking using detection-guided optimization. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3213–3221

    Google Scholar 

  32. Zhou X, Wan Q, Zhang W, Xue X, Wei Y (2016) Model-based deep hand pose estimation. arXiv:1606.06854

  33. Oberweger M, Wohlhart P, Lepetit V (2015) Training a feedback loop for hand pose estimation. In: Proceedings of the IEEE international conference on computer vision, pp 3316–3324

    Google Scholar 

  34. Zimmermann C, Brox T (2017) Learning to estimate 3d hand pose from single rgb images. In: International conference on computer vision

    Google Scholar 

  35. Oberweger M, Wohlhart P, Lepetit V (2015) Hands deep in deep learning for hand pose estimation. arXiv:1502.06807

  36. Athitsos V, Sclaroff S (2003) Estimating 3d hand pose from a cluttered image. In Proceedings 2003 IEEE computer society conference on computer vision and pattern recognition, vol 2. IEEE, ppD II–432

    Google Scholar 

  37. Yuan S, Garcia-Hernando G, Stenger B, Moon G, Yong Chang J, Mu Lee K, Molchanov P, Kautz J, Honari S, Ge L et al (2017) 3d hand pose estimation: From current achievements to future goals. arXiv:1712.03917

  38. Wang R, Zhou K, Snyder J, Liu X, Bao H, Peng Q, Guo B (2006) Variational sphere set approximation for solid objects. Vis Comput 22(9–11):612–621

    Article  Google Scholar 

  39. Taylor J, Stebbing R, Ramakrishna V, Keskin C, Shotton J, Izadi S, Hertzmann A, Fitzgibbon A (2014) User-specific hand modeling from monocular depth sequences. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 644–651

    Google Scholar 

  40. Oikonomidis I, Kyriazis N, Argyros AA (2010) Markerless and efficient 26-dof hand pose recovery. In: Asian conference on computer vision. Springer, pp 744–757

    Google Scholar 

  41. Oikonomidis I, Kyriazis N, Argyros AA (2012) Tracking the articulated motion of two strongly interacting hands. In: 2012 IEEE conference on computer vision and pattern recognition (CVPR). IEEE, pp 1862–1869

    Google Scholar 

  42. Makris A, Argyros A (2015) Model-based 3d hand tracking with on-line hand shape adaptation. In: Proceedings of BMVC, pp 77–1

    Google Scholar 

  43. Melax S, Keselman L, Orsten S (2013) Dynamics based 3d skeletal hand tracking. In: Proceedings of graphics interface 2013. Canadian Information Processing Society, pp 63–70

    Google Scholar 

  44. Sridhar S, Oulasvirta A, Theobalt C (2013) Interactive markerless articulated hand motion tracking using rgb and depth data. In: Proceedings of the IEEE international conference on computer vision, pp 2456–2463

    Google Scholar 

  45. Khamis S, Taylor J, Shotton J, Keskin C, Izadi S, Fitzgibbon A (2015) Learning an efficient model of hand shape variation from depth images. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2540–2548

    Google Scholar 

  46. Joseph Tan D, Cashman T, Taylor J, Fitzgibbon A, Tarlow D, Khamis S, Izadi S, Shotton J (2016) Fits like a glove: Rapid and reliable hand shape personalization. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5610–5619

    Google Scholar 

  47. Helten T, Baak A, Bharaj G, Müller M, Seidel HP, Theobalt C (2013) Personalization and evaluation of a real-time depth-based full body tracker. In: 2013 international conference on 3D vision-3DV 2013. IEEE, pp 279–286

    Google Scholar 

  48. Makris A, Argyros A (September 2015) Model-based 3d hand tracking with on-line shape adaptation. In: Jones MW, Xie MX, Tam GK (eds) Proceedings of the british machine vision conference (BMVC). BMVA Press, pages 77.1–77.12

    Google Scholar 

  49. Tompson J, Stein M, Lecun Y, Perlin K (2014) Real-time continuous pose recovery of human hands using convolutional networks. ACM Trans Graph (ToG) 33(5):169

    Article  Google Scholar 

  50. Kennedy, J (2010) Particle swarm optimization. In: Encyclopedia of machine learning. Springer, pp 760–766

    Google Scholar 

  51. Banks A, Vincent J, Anyakoha C (2007) A review of particle swarm optimization. Part I: background and development. Nat Comput 6(4):467–484

    Article  MathSciNet  Google Scholar 

  52. Coello CAC, Pulido GT, Lechuga MS (2004) Handling multiple objectives with particle swarm optimization. IEEE Trans Evol Comput 8(3):256–279

    Article  Google Scholar 

  53. Reyes-Sierra M, Coello CC (2006) Multi-objective particle swarm optimizers: a survey of the state-of-the-art. Int J Comput Intell Res 2(3):287–308

    Google Scholar 

  54. Ouhaddi H, Horain P (1999) 3d hand gesture tracking by model registration. In: workshop on synthetic-natural hybrid coding and three dimensional imaging, pp 70–73

    Google Scholar 

  55. Ueda E, Matsumoto Y, Imai M, Ogasawara T (2003) A hand-pose estimation for vision-based human interfaces. IEEE Trans Ind Electron 50(4):676–684

    Article  Google Scholar 

  56. Wolpert DH, Macready WG (1997) No free lunch theorems for optimization. IEEE Trans Evol Comput 1(1):67–82, 1997

    Article  Google Scholar 

  57. Deb K, Srinivasan A (2006) Innovization: innovating design principles through optimization. In: Proceedings of the 8th annual conference on Genetic and evolutionary computation. ACM, pp 1629–1636

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Torrens University Australia, Fortitude Valley, Brisbane, QLD, Australia

    Shahrzad Saremi & Seyedali Mirjalili

Authors
  1. Shahrzad Saremi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seyedali Mirjalili
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shahrzad Saremi .

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Saremi, S., Mirjalili, S. (2020). A Survey of Hand Posture Estimation Techniques and Optimisation Algorithms. In: Optimisation Algorithms for Hand Posture Estimation. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-9757-8_2

Download citation

Publish with us

Policies and ethics

Search

Navigation