The Camera-Driven Interactive Table

One emerging application of computing technology is that of interactive rooms and furniture. For instance, Interactive Tables allow for a workspace that is intuitive, natural, and conducive to creating multi-user collaborative work environments. Although several interactive table prototypes have been developed, we have engineered a method using a computer vision system instead of touch screen technology, which allows increased flexibility to the end user because of its ability to ignore or even make use of objects placed upon the table and its decreased likelihood of accidental input. In this work we present a method for implementing such a camera-driven interactive table with a ceiling-mounted camera and demonstrate some of its potential uses. The vision system makes use of a novel hand detection and segmentation technique designed to be tolerant of any level of background complexity on the display and any reasonable range of indoor lighting conditions, thus allowing the highest level of freedom to the end user. It searches the results of multi-scale line and curve finding systems to locate thimble-shaped finger models, marking them as candidate fingers and performing a set of geometric and texture-based tests on each to remove false positives. Finally, it groups finger detections that are similar to each other in location and appearance, while allowing the reintroduction of weak candidates that are supported by strong neighbors, into hand detections with finger and palm locations. Results demonstrate the system's ability extract enough information from images of hands in very complex backgrounds to allow for finger and palm placement recognition

[1]  Takeo Kanade,et al.  Visual Tracking of High DOF Articulated Structures: an Application to Human Hand Tracking , 1994, ECCV.

[2]  Rómer Rosales,et al.  3D Hand Pose Reconstruction Using Specialized Mappings , 2001, ICCV.

[3]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[4]  John F. Canny.  A Variational Approach to Edge Detection , 1983, AAAI.

[5]  wikiTable: finger driven interaction for collaborative knowledge-building workspaces , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[6]  Yoshiaki Shirai,et al.  Real-time 3D hand posture estimation based on 2D appearance retrieval using monocular camera , 2001, Proceedings IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems.

[7]  Ramakant Nevatia,et al.  Stochastic human segmentation from a static camera , 2002, Workshop on Motion and Video Computing, 2002. Proceedings..

[8]  Vladimir Pavlovic,et al.  Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Björn Stenger,et al.  Hand Pose Estimation Using Hierarchical Detection , 2004, ECCV Workshop on HCI.

[10]  Ying Wu,et al.  Capturing articulated human hand motion: a divide-and-conquer approach , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[11]  Ying Wu,et al.  View-independent recognition of hand postures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[12]  Tsuhan Chen,et al.  Hand tracking using spatial gesture modeling and visual feedback for a virtual DJ system , 2002, Proceedings. Fourth IEEE International Conference on Multimodal Interfaces.

[13]  Richard Bowden,et al.  A boosted classifier tree for hand shape detection , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..

[14]  Allen R. Hanson,et al.  Extracting Straight Lines , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[15]  Stan Sclaroff,et al.  Automatic 2D Hand Tracking in Video Sequences , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[16]  Jefferson Y. Han.  Multi-touch interaction research , 2006, International Conference on Computer Graphics and Interactive Techniques.

[17]  Andrew D. Wilson.  PlayAnywhere: a compact interactive tabletop projection-vision system , 2005, UIST.

[18]  Lars Bretzner,et al.  Hand gesture recognition using multi-scale colour features, hierarchical models and particle filtering , 2002, Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition.

[19]  Mathias Kölsch,et al.  Robust hand detection , 2004, Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings..