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Jacobs DW, Belhumeur PN, Basri R.  1998.  Comparing images under variable illumination. Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on. :610-617.
Jacobs DW, Chennubhotla C.  1994.  Segmenting independently moving, noisy points. Motion of Non-Rigid and Articulated Objects, 1994., Proceedings of the 1994 IEEE Workshop on. :96-103.
Jacobs DW, Shirdhonkar S.  2005.  Non-negative lighting and specular object recognition. Proc. of IEEE International Conference on Computer Vision. 2
Jacobs DW.  1991.  Optimal matching of planar models in 3D scenes. Computer Vision and Pattern Recognition, 1991. Proceedings CVPR '91., IEEE Computer Society Conference on. :269-274.
Jacobs DW.  1987.  GROPER: A Grouping Based Object Recognition System for Two-Dimensional Objects. IEEE Workshop on Computer Vision. :164-169.
Jacobs DW, Weinshall D, Gdalyahu Y.  2000.  Classification with nonmetric distances: image retrieval and class representation. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 22(6):583-600.
Jacobs DW, Lindenbaum M, August J, Zucker SW, Ben-Shahar O, Zucker SW, Tuytelaars T, Turina A, Van Gool L, Mahamud S.  2003.  Special section on perceptual organization in computer vision.
Jacobs DW, Basri R.  1997.  3-D to 2-D recognition with regions. Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on. :547-553.
Jacobs DW.  2003.  BAYESIAN AND STATISTICAL APPROACHES TO VISION-Natural Image Statistics and Perceptual Inference-What makes viewpoint-invariant properties perceptually salient? Journal of the Optical Society of America-A-Optics Image Science and Vision. 20(7):1304-1320.
Jacobs DW.  2003.  Perceptual Completion and Memory. Perceptual organization in vision: behavioral and neural perspectivesPerceptual organization in vision: behavioral and neural perspectives. :403-403.
Jacobs DW, Weinshall D, Gdalyahu Y.  2000.  Class representation and image retrieval with non-metric distances. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). 22(583-600):1-1.
Jacobs DW.  1996.  The space requirements of indexing under perspective projections. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 18(3):330-333.
Jacobs DW.  1993.  Recognizing 3-D objects using 2-D images.
Jacobs DW.  1997.  Linear fitting with missing data: applications to structure-from-motion and to characterizing intensity images. Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on. :206-212.
Jacobs DW.  2003.  What makes viewpoint-invariant properties perceptually salient? Journal of the Optical Society of America A. 20(7):1304-1320.
Jacobs DW, Malik J, Nevatia R.  2000.  Breakout Session Report: Principles and Methods. Perceptual Organization for Artificial Vision Systems. :17-28.
Jacobs DW, Basri R T W I.  2007.  Object recognition using linear subspaces. EP20010117763(EP1204069)
Jacobs DW.  2001.  Linear Fitting with Missing Data for Structure-from-Motion. Computer Vision and Image Understanding. 82(1):57-81.
Jacobs DW.  2001.  Perceptual organization as generic object recognition. From Fragments to Objects Segmentation and Grouping in VisionFrom Fragments to Objects Segmentation and Grouping in Vision. Volume 130:295-329.
Jacobs DW.  1996.  Robust and efficient detection of salient convex groups. Pattern Analysis and Machine Intelligence, IEEE Transactions on. 18(1):23-37.
Jacobs DW, Alter TD.  1994.  Uncertainty Propagation in Model-Based Recognition..
Jacobs DW, Getoor L.  2008.  Statistical Relational Learning as an Enabling Technology for Data Acquisition and Data Fusion in Heterogeneous Sensor Networks.
Jacobs DW.  1993.  2D images of 3-D oriented points. Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on. :226-232.
Jacobs DW.  1997.  Matching 3-D models to 2-D images. International Journal of Computer Vision. 21(1):123-153.
Jacobs DW.  2000.  What makes viewpoint invariant properties perceptually salient?: A computational perspective Perceptual organization for artificial vision systems. :121-138.

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