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Outline

Title
Abstract
Introduction
Related Work
Calibration Method
Using Tracker Data
Design
Results
Discussion and Design Considerations
Limitations
Conclusions and Future Work
References
All Topics
Computer Science
Computer Vision

Creepy Tracker Toolkit for Context-aware Interfaces

Profile image of Joaquim JorgeJoaquim Jorge

2017, Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces

https://doi.org/10.1145/3132272.3134113
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10 pages

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Abstract

Figure 1. Creepy Tracker is an open-source toolkit that provides spatial information about people and interactive surfaces. To do this, it resorts to multiple depth sensing cameras (A, B). It helps the design of systems that handle, for instance, (C) interactive tabletops, (D) vertical surfaces, (E) floor projections and even capture avatars for (F) telepresence or (G) virtual reality.

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Visual tracking in unconstrained environments is very challenging due to the existence of several sources of varieties such as changes in appearance, varying lighting conditions, cluttered background, and frame-cuts. A major factor causing tracking failure is the emergence of regions having similar appearance as the target. It is even more challenging when the target leaves the field of view (FoV) leading the tracker to follow another similar object, and not reacquire the right target when it reappears. This paper presents a method to address this problem by exploiting the context on-the-fly in two terms: Distracters and Supporters. Both of them are automatically explored using a sequential randomized forest, an online template-based appearance model, and local features. Distracters are regions which have similar appearance as the target and consistently co-occur with high confidence score. The tracker must keep tracking these distracters to avoid drifting. Supporters, on the other hand, are local key-points around the target with consistent co-occurrence and motion correlation in a short time span. They play an important role in verifying the genuine target. Extensive experiments on challenging real-world video sequences show the tracking improvement when using this context information. Comparisons with several state-of-the-art approaches are also provided.

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DOI 10.1007/s00138-012-0408-6 ORIGINAL PAPER Multicamera human detection and tracking supporting natural interaction with large-scale displays
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2013

This paper presents a computer vision system that supports non-instrumented, location-based interaction of multiple users with digital representations of large-scale artifacts. The proposed system is based on a camera network that observes multiple humans in front of a very large display. The acquired views are used to volumetrically reconstruct and track the humans robustly and in real time, even in crowded scenes and challenging human configurations. Given the frequent and accurate monitoring of humans in space and time, a dynamic and personalized textual/graphical annotation of the display can be achieved based on the location and the walk-through trajectory of each visitor. The proposed system has been successfully deployed in an archaeological museum, offering its visitors the capability to interact with and explore a digital representation of an ancient wall painting. This installation permits an extensive evaluation of the proposed system in terms of tracking robustness, comp...

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FittsFace: Exploring Navigation and Selection Methods for Facial Tracking
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An experimental application called FittsFace was designed according to ISO 9241-9 to compare and evaluate facial tracking and camera-based input on mobile devices for accessible computing. A user study with 12 participants employed a Google Nexus 7 tablet to test two facial navigation methods (positional, rotational) and three selection methods (dwell, smile, blink). Positional navigation was superior, with a mean throughput of 0.58 bits/second (bps), roughly 1.5× the value observed for rotational navigation. Blink selection was the least accurate selection method, with a 28.7% error rate. The optimal combination was positional+smile, with a mean throughput of 0.60 bps and the lowest tracking drop rate.

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Abstract Proximity Toolkit is a toolkit that simplifies the exploration of interaction techniques based on proximity and orientations of people, tools, and large digital surfaces. ViconFace is a playful demonstration application built atop of this toolkit. A cartoon face on a large display tracks a person moving around it, where it visually and verbally responds to that person's proximity, orientation and wand use. The accompanying video illustrates all this in action.

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Chapter 9 Tracking
Virtual Reality

2016

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Third IEEE and ACM International Symposium on Mixed and Augmented Reality, 2004

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References (44)

  1. Aggarwal, J. K., and Ryoo, M. S. Human activity analysis: A review. ACM Computing Surveys (CSUR) 43, 3 (2011), 16.
  2. Annett, M., Grossman, T., Wigdor, D., and Fitzmaurice, G. Medusa: a proximity-aware multi-touch tabletop. In Proceedings of the 24th annual ACM symposium on User interface software and technology, ACM (2011), 337-346.
  3. Antifakos, S., and Schiele, B. Beyond position awareness. Personal and Ubiquitous Computing 6, 5-6 (2002), 313-317.
  4. Ark, W. S., and Selker, T. A look at human interaction with pervasive computers. IBM systems journal 38, 4 (1999), 504-507.
  5. Augsten, T., Kaefer, K., Meusel, R., Fetzer, C., Kanitz, D., Stoff, T., Becker, T., Holz, C., and Baudisch, P. Multitoe: High-precision interaction with back-projected floors based on high-resolution multi-touch input. In Proceedings of the 23Nd Annual ACM Symposium on User Interface Software and Technology, UIST '10, ACM (New York, NY, USA, 2010), 209-218.
  6. Azimi, M. Skeletal joint smoothing white paper. Tech. rep., 2012. http://msdn.microsoft.com/en-us/ library/jj131429.aspx.
  7. Ballendat, T., Marquardt, N., and Greenberg, S. Proxemic interaction: Designing for a proximity and orientation-aware environment. In ACM International Conference on Interactive Tabletops and Surfaces, ITS '10, ACM (New York, NY, USA, 2010), 121-130.
  8. Beck, S., Kunert, A., Kulik, A., and Froehlich, B. Immersive group-to-group telepresence. IEEE Transactions on Visualization and Computer Graphics 19, 4 (2013), 616-625.
  9. Bolt, R. A. Put-that-there: Voice and gesture at the graphics interface. In Proceedings of the 7th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH '80, ACM (New York, NY, USA, 1980), 262-270.
  10. Dey, A. K., Abowd, G. D., and Salber, D. A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human-computer interaction 16, 2 (2001), 97-166.
  11. Fails, J. A., and Olsen, J. D. Light widgets: interacting in every-day spaces. In Proceedings of the 7th international conference on Intelligent user interfaces, ACM (2002), 63-69.
  12. Grønbaek, K., Iversen, O. S., Kortbek, K. J., Nielsen, K. R., and Aagaard, L. Igamefloor: A platform for co-located collaborative games. In Proceedings of the International Conference on Advances in Computer Entertainment Technology, ACE '07, ACM (New York, NY, USA, 2007), 64-71.
  13. Gugenheimer, J., Stemasov, E., Frommel, J., and Rukzio, E. Sharevr: Enabling co-located experiences for virtual reality between hmd and non-hmd users. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI '17, ACM (New York, NY, USA, 2017), 4021-4033.
  14. Hall, E. T. The hidden dimension. Doubleday & Co, 1966.
  15. Harris, A., Rick, J., Bonnett, V., Yuill, N., Fleck, R., Marshall, P., and Rogers, Y. Around the table: Are multiple-touch surfaces better than single-touch for children's collaborative interactions? In Proceedings of the 9th international conference on Computer supported collaborative learning-Volume 1, International Society of the Learning Sciences (2009), 335-344.
  16. Insafutdinov, E., Pishchulin, L., Andres, B., Andriluka, M., and Schiele, B. Deepercut: A deeper, stronger, and faster multi-person pose estimation model. arXiv preprint arXiv:1605.03170 (2016).
  17. Jokela, T., Ojala, J., and Olsson, T. A diary study on combining multiple information devices in everyday activities and tasks. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI '15, ACM (New York, NY, USA, 2015), 3903-3912.
  18. Jones, B., Sodhi, R., Murdock, M., Mehra, R., Benko, H., Wilson, A., Ofek, E., MacIntyre, B., Raghuvanshi, N., and Shapira, L. Roomalive: Magical experiences enabled by scalable, adaptive projector-camera units. In Proceedings of the 27th Annual ACM Symposium on User Interface Software and Technology, UIST '14, ACM (New York, NY, USA, 2014), 637-644.
  19. Marquardt, N., Ballendat, T., Boring, S., Greenberg, S., and Hinckley, K. Gradual engagement: Facilitating information exchange between digital devices as a function of proximity. In Proceedings of the 2012 ACM International Conference on Interactive Tabletops and Surfaces, ITS '12, ACM (New York, NY, USA, 2012), 31-40.
  20. Marquardt, N., Diaz-Marino, R., Boring, S., and Greenberg, S. The proximity toolkit: Prototyping proxemic interactions in ubiquitous computing ecologies. In Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, UIST '11, ACM (New York, NY, USA, 2011), 315-326.
  21. Marquardt, N., Hinckley, K., and Greenberg, S. Cross-device interaction via micro-mobility and f-formations. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology, UIST '12, ACM (New York, NY, USA, 2012), 13-22.
  22. Marquardt, N., Jota, R., Greenberg, S., and Jorge, J. The continuous interaction space: interaction techniques unifying touch and gesture on and above a digital surface. Human-Computer Interaction-INTERACT 2011 (2011), 461-476.
  23. Marshall, P., Hornecker, E., Morris, R., Dalton, N. S., and Rogers, Y. When the fingers do the talking: A study of group participation with varying constraints to a tabletop interface. In Horizontal Interactive Human Computer Systems, 2008. TABLETOP 2008. 3rd IEEE International Workshop on, IEEE (2008), 33-40.
  24. Matthews, T., Dey, A. K., Mankoff, J., Carter, S., and Rattenbury, T. A toolkit for managing user attention in peripheral displays. In Proceedings of the 17th annual ACM symposium on User interface software and technology, ACM (2004), 247-256.
  25. Mendes, D., Relvas, F., Ferreira, A., and Jorge, J. The benefits of dof separation in mid-air 3d object manipulation. In Proceedings of the 22Nd ACM Conference on Virtual Reality Software and Technology, VRST '16, ACM (New York, NY, USA, 2016), 261-268.
  26. Orts-Escolano, S., Rhemann, C., Fanello, S., Chang, W., Kowdle, A., Degtyarev, Y., Kim, D., Davidson, P. L., Khamis, S., Dou, M., et al. Holoportation: Virtual 3d teleportation in real-time. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology, ACM (2016), 741-754.
  27. Pejsa, T., Kantor, J., Benko, H., Ofek, E., and Wilson, A. Room2room: Enabling life-size telepresence in a projected augmented reality environment. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, ACM (2016), 1716-1725.
  28. Pierce, J. S., Forsberg, A. S., Conway, M. J., Hong, S., Zeleznik, R. C., and Mine, M. R. Image plane interaction techniques in 3d immersive environments. In Proceedings of the 1997 symposium on Interactive 3D graphics, ACM (1997), 39-ff.
  29. Raskar, R., Welch, G., Cutts, M., Lake, A., Stesin, L., and Fuchs, H. The office of the future: A unified approach to image-based modeling and spatially immersive displays. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH '98, ACM (New York, NY, USA, 1998), 179-188.
  30. Rekimoto, J., and Nagao, K. The world through the computer: Computer augmented interaction with real world environments. In Proceedings of the 8th annual ACM symposium on User interface and software technology, ACM (1995), 29-36.
  31. Schilit, B., Adams, N., and Want, R. Context-aware computing applications. In Mobile Computing Systems and Applications, 1994. WMCSA 1994. First Workshop on, IEEE (1994), 85-90.
  32. Seyed, T., Azazi, A., Chan, E., Wang, Y., and Maurer, F. Sod-toolkit: A toolkit for interactively prototyping and developing multi-sensor, multi-device environments. In Proceedings of the 2015 International Conference on Interactive Tabletops & Surfaces, ITS '15, ACM (New York, NY, USA, 2015), 171-180.
  33. Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., and Moore, R. Real-time human pose recognition in parts from single depth images. Communications of the ACM 56, 1 (2013), 116-124.
  34. Slater, M., and Usoh, M. Body centred interaction in immersive virtual environments. Artificial life and virtual reality 1, 1994 (1994), 125-148.
  35. Sousa, M., Mendes, D., Ferreira, A., Pereira, J. M., and Jorge, J. Eery space: facilitating virtual meetings through remote proxemics. In Human-Computer Interaction, Springer, Cham (2015), 622-629.
  36. Tang, R., Alizadeh, H., Tang, A., Bateman, S., and Jorge, J. A. Physio@home: Design explorations to support movement guidance. In CHI '14 Extended Abstracts on Human Factors in Computing Systems, CHI EA '14, ACM (New York, NY, USA, 2014), 1651-1656.
  37. Vermeulen, J., Luyten, K., Coninx, K., Marquardt, N., and Bird, J. Proxemic flow: Dynamic peripheral floor visualizations for revealing and mediating large surface interactions. In Human-Computer Interaction, Springer (2015), 264-281.
  38. Vogel, D., and Balakrishnan, R. Interactive public ambient displays: Transitioning from implicit to explicit, public to personal, interaction with multiple users. In Proceedings of the 17th Annual ACM Symposium on User Interface Software and Technology, UIST '04, ACM (New York, NY, USA, 2004), 137-146.
  39. Weiser, M. The computer for the 21st century. Scientific american 265, 3 (1991), 94-104.
  40. Weiser, M. The computer for the 21st century. IEEE pervasive computing 1, 1 (2002), 19-25.
  41. Wilson, A. D. Depth-sensing video cameras for 3d tangible tabletop interaction. In Horizontal Interactive Human-Computer Systems, 2007. TABLETOP'07. Second Annual IEEE International Workshop on, IEEE (2007), 201-204.
  42. Wilson, A. D., and Benko, H. Combining multiple depth cameras and projectors for interactions on, above and between surfaces. In Proceedings of the 23nd annual ACM symposium on User interface software and technology, ACM (2010), 273-282.
  43. Wilson, A. D., and Benko, H. Crossmotion: Fusing device and image motion for user identification, tracking and device association. In Proceedings of the 16th International Conference on Multimodal Interaction, ICMI '14, ACM (New York, NY, USA, 2014), 216-223.
  44. Wu, C.-J., Houben, S., and Marquardt, N. Eaglesense: Tracking people and devices in interactive spaces using real-time top-view depth-sensing. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI '17, ACM (New York, NY, USA, 2017), 3929-3942.

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