Team for Research in
Ubiquitous Secure Technology

Citation
Jeremy Schiff, Marci Meingast, Deirdre Mulligan, Shankar Sastry, Ken Goldberg. " Respectful cameras: detecting visual markers in real-time to address privacy concerns". Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, 971-978, October, 2007.

Abstract
To address privacy concerns with digital video surveillance cameras, we propose a practical, real-time approach that preserves the ability to observe actions while obscuring individual identities. In our proposed Respectful Cameras system, people who wish to remain anonymous agree to wear colored markers such as a hat or vest. The system automatically tracks these markers using statistical learning and classification to infer the location and size of each face and then inserts elliptical overlays. Our objective is to obscure the face of each individual wearing a marker, while minimizing the overlay area in order to maximize the remaining observable region of the scene. Our approach incorporates a visual color-tracker based on a 9 dimensional color-space by using a Probabilistic AdaBoost classifier with axis-aligned hyperplanes as weak-learners. We then use Particle Filtering to incorporate interframe temporal information. We present experiments illustrating the performance of our system in both indoor and outdoor settings, where occlusions, multiple crossing targets, and lighting changes occur. Results suggest that the Respectful Camera system can reduce false negative rates to acceptable levels (under 2%).

Electronic downloads

• http://dx.doi.org/10.1109/IROS.2007.4399122. (See also Jeremy Schiff's Respectful Cameras Project Page)

• HTML

  Jeremy Schiff, Marci Meingast, Deirdre Mulligan, Shankar
  Sastry, Ken Goldberg. <a
  href="http://www.truststc.org/pubs/319.html">
  Respectful cameras: detecting visual markers in real-time to
  address privacy concerns</a>, Intelligent Robots and
  Systems, 2007. IROS 2007. IEEE/RSJ International Conference
  on, 971-978, October, 2007.

• Plain text

  Jeremy Schiff, Marci Meingast, Deirdre Mulligan, Shankar
  Sastry, Ken Goldberg. " Respectful cameras: detecting
  visual markers in real-time to address privacy
  concerns". Intelligent Robots and Systems, 2007. IROS
  2007. IEEE/RSJ International Conference on, 971-978,
  October, 2007.

• BibTeX

  @inproceedings{SchiffMeingastMulliganSastryGoldberg07_RespectfulCamerasDetectingVisualMarkersInRealtimeTo,
      author = {Jeremy Schiff and Marci Meingast and Deirdre
                Mulligan and Shankar Sastry and Ken Goldberg},
      title = { Respectful cameras: detecting visual markers in
                real-time to address privacy concerns},
      booktitle = {Intelligent Robots and Systems, 2007. IROS 2007.
                IEEE/RSJ International Conference on},
      pages = {971-978},
      month = {October},
      year = {2007},
      abstract = {To address privacy concerns with digital video
                surveillance cameras, we propose a practical,
                real-time approach that preserves the ability to
                observe actions while obscuring individual
                identities. In our proposed Respectful Cameras
                system, people who wish to remain anonymous agree
                to wear colored markers such as a hat or vest. The
                system automatically tracks these markers using
                statistical learning and classification to infer
                the location and size of each face and then
                inserts elliptical overlays. Our objective is to
                obscure the face of each individual wearing a
                marker, while minimizing the overlay area in order
                to maximize the remaining observable region of the
                scene. Our approach incorporates a visual
                color-tracker based on a 9 dimensional color-space
                by using a Probabilistic AdaBoost classifier with
                axis-aligned hyperplanes as weak-learners. We then
                use Particle Filtering to incorporate interframe
                temporal information. We present experiments
                illustrating the performance of our system in both
                indoor and outdoor settings, where occlusions,
                multiple crossing targets, and lighting changes
                occur. Results suggest that the Respectful Camera
                system can reduce false negative rates to
                acceptable levels (under 2%).},
      URL = {http://www.truststc.org/pubs/319.html}
  }
  

Posted by Christopher Brooks on 29 Feb 2008.
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