1 / 27

Hands and face tracking for VR applications

This paper presents a comprehensive approach to hands and face tracking in virtual reality applications, key for enabling intuitive user navigation in immersive 3D spaces. It outlines an algorithm that detects skin color pixels and associates data for accurate tracking of hands and face movements. The paper also discusses the visualization of 3D data using the H-Anim standard, allowing for collaboration with VRML models. Concluding with future directions, it emphasizes the potential for improved human-computer interaction through these methodologies.

maisie-joseph
Télécharger la présentation

Hands and face tracking for VR applications

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Hands and face tracking for VR applications Javier Varona, Jose’ M. Buades, Francisco J. Perales Unidad de Gra´ficos y Visio´n por Ordenador, Dept. de matematiques i Informatica, Universitat de les Illes Balears (UIB), crta. Valldemossa km. 7,5, 07122 Palma de Mallorca, Spain Adviser: Chih-Hung Lin Date:2010/12/14 Speaker: Chin He Hsu

  2. Outline 1.Introduction 2. Hands and face tracking algorithm 3.Visualization using H-Anim 4.Conclusion and future work

  3. 1.Introduction • In order to allow a user to navigate in a 3D-space

  4. Interactive 3D-space

  5. system must detect a new user • entering into the system’s environment • analyse him to set parameters • tracking interesting regions

  6. 2. Hands and face tracking algorithm • tracking problem lies in identifying both hands and face in each image • detect skin-colour pixels • data association algorithm

  7. 2.1. Skin-colour segmentation module • skin-colour detection • necessary to model the actor’s skin-colour in a previous step

  8. skin-colour sample • transform these pixels from the RGB-space to HSL-space • hue and saturation values contain the chroma information • two main problems • human skin hue values are near the red colour • saturation values are near 0

  9. skin-colour distribution • Gaussian model

  10. Contours of skin-colour blobs after the connected components process

  11. 2.2. Data association module

  12. Next linear scheme of prediction • that an extreme limb will maintain the same velocity

  13. Set of hypothesis

  14. define an approximation to the distance from the x image pixel to the hypothesis h

  15. calculating the angle • Normalized image pixel and the hypothesis centre

  16. distance between an image pixel and a hypothesis • if d( x ,h)<=0 , then x is inside the hypothesis h ,if d( x ,h)>0 , then x is outside the hypothesis h

  17. a blob with empty intersection with all hypotheses • a pixel x of a blob is inside a limb hypothesis

  18. Occlusion case solved using multiple labelling

  19. 2.3. 3D-point reconstruction

  20. Complete procedure: color segmentation, data association and 3D reconstruction

  21. 3. Visualization using H-Anim • H-Anim (humanoid animation) • we use the H-Anim standard, this way we can collaborate with standard VRML (Virtual Reality Modeling Language ) models

  22. 3D position

  23. 4. Conclusion and future work • proposed a new system • human–computer interaction • future work

More Related