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Andrew Stein
PhD Student

Email address: anstein@cmu.edu
Office: EDSH 216
Phone: (412) 268-1420

Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213

For more information, see my personal homepage.

Jump to: Research interests | Keywords | Labs & groups | Publications

My general research focus is in the field of Computer Vision. I am currently researching the use of object boundary information in object recognition. I am interested in the use of limited 3D information for augmenting current 2D-only recognition approaches, but I hope to avoid the computation, complexity, and potential overkill of full 3D reconstruction/ modeling. To that end, I have developed methods for incorporating object boundary information into feature-based object recognition, resulting in an augmentation of the popular Scale Invariant Feature Transform (SIFT) method which we call the Background and Scale Invariant Feature Transform (BSIFT). Now, we are developing robust and accurate methods for finding object boundaries. We also hope to incorporate shape information in the future.

In the past, I have also explored topics such as real-time tracking, assembling 3D object models via ICP, colored structured light for range imaging, and sequential structure from motion (SFM). I am also interested in the problem of mobile manipulation: building robots capable not only of navigating in an environment, but also interacting with that environment. Applications of computer vision and robotics that interest me include assisting people with disabilities, space exploration, search and rescue, and medicine.

3-D perception, computer vision, machine learning, manipulation, mobile robots, object recognition, range data, and statistics

• Vision and Mobile Robotics Lab - Our group studies fundamental problems of Computer Vision and ground mobile robotics.

• Towards Unsupervised Whole-Object Segmentation: Combining Automated Matting with Boundary Detection
  A. Stein, T. Stepleton, and M. Hebert
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June, 2008. [Abstract]
  Download: pdf [2537 KB] copyrighted

• Occlusion Boundaries: Low-Level Detection to High-Level Reasoning
  A. Stein
  doctoral dissertation, tech. report CMU-RI-TR-08-06, Robotics Institute, Carnegie Mellon University, May, 2008. [Abstract]
  Download: pdf [28172 KB] copyrighted

• Learning to Find Object Boundaries Using Motion Cues
  A. Stein, D. Hoiem, and M. Hebert
  IEEE International Conference on Computer Vision (ICCV), October, 2007. [Abstract]
  Download: pdf [661 KB] copyrighted

• Recovering Occlusion Boundaries from a Single Image
  D. Hoiem, A. Stein, A.A. Efros, and M. Hebert
  International Conference on Computer Vision (ICCV), October, 2007. [Abstract]
  Download: pdf [2337 KB] copyrighted

• Combining Local Appearance and Motion Cues for Occlusion Boundary Detection
  A. Stein and M. Hebert
  British Machine Vision Conference (BMVC), September, 2007. [Abstract]
  Download: pdf [386 KB] copyrighted

• Computer Vision on Mars
  L. Matthies, M. Maimone, A. Johnson, Y. Cheng, R. Willson, C. Villalpando, S. Goldberg, A. Huertas, A. Stein, and A. Angelova
  International Journal of Computer Vision, 2007. [Abstract]
  Download: pdf [1707 KB] copyrighted

• Local Detection of Occlusion Boundaries in Video
  A. Stein and M. Hebert
  British Machine Vision Conference, September, 2006. [Abstract]
  Download: pdf [481 KB] copyrighted

• How multirobot systems research will accelerate our understanding of social animal behavior
  T. Balch, F. Dellaert, A. Feldman, A. Guillory, C. Isbell, Z. Khan, S. Pratt, A. Stein, and H. Wilde
  Proceedings of the IEEE, Vol. 94, No. 7, July, 2006, pp. 1445-1463. [Abstract]
  Download: pdf [4633 KB] copyrighted

• Using Spatio-Temporal Patches for Simultaneous Estimation of Edge Strength, Orientation, and Motion
  A. Stein and M. Hebert
  Beyond Patches Workshop at IEEE Conference on Computer Vision and Pattern Recognition, June, 2006. [Abstract]
  Download: pdf [1279 KB] copyrighted

• Attenuating Stereo Pixel-Locking via Affine Window Adaptation
  A. Stein, A. Huertas, and L. Matthies
  IEEE International Conference on Robotics and Automation, May, 2006, pp. 914 - 921. [Abstract]
  Download: pdf [580 KB] copyrighted