References

1

Martin Glenn, and Shah, M. Lipreading Using Optical Flow. In Proc. National Conference on Undergraduate Research, March 1992.

2

Cédras, C., and Shah, M. A survey of motion analysis from moving light displays. In IEEE Conference on Computer Vision and Pattern Recognition, 1994.

3

Cipolla, R.,Okamoto, Y. and Kuno, Y. Robust structure from motion using motion parallax. In IEEE Proceedings on International Conference on Computer Vision, 1993.

4

E. Costello. Signing: How to Speak With Your Hands. Bantam Books, New York, 1983.

5

Cryer, J., Tsai, P-S, and Shah, M. . Integration of shape from x modules: Combining stereo and shading. In IEEE Conference on Computer Vision and Pattern Recognition, 1993.

6

Darrell, T., and Pentland, A. Space-time gestures. In CVPR, pages 335-340. IEEE, 1993.

7

Davis, J., and Shah, M. Recognizing hand gestures. In ECCV, pages 331-340, May 1994.

8

Davis, J., and Shah, M. Three-dimensional gesture recognition. In Asilomar Conference on Signals, Systems, And Computers, 1994.

9

Davis, J., and Shah, M. Visual gesture recognition. IEE Proceedings Vision, Image and Signal Processing, 1994.

10

Fukumoto, M., Mase, K., and Suenaga, Y. Real-time detection of pointing actions for a glove-free interface. In IAPR Workshop on Machine Vision Applications, pages 473-476, December 1992.

11

Gould, K., and Shah, M. The trajectory primal sketch. In Conference on Computer Vision and Pattern Recognition, pages 79-85, San Diego: IEEE Computer Society, June, 1989.

12

Gould, K., Rangarajan, K., and Shah, M. Advances in image analysis. chapter Detection and Representation of Events in Motion Trajectories. SPIE Press, 1992.

13

Hackett, J., and Shah, M. Mutli-sensor fusion. In International Conference on Robotics and Automation, pages 1324-1330. IEEE, May, 1990.

14

Hackett, J., Lavoie, M., and Shah, M. Object recognition using multiple sensors. Journal of Information Sciences and Technology, 1992.

15

Hackett, J., Lavoie, M., and Shah, M. Object recognition using multiple sensors. In SPIE Advances in Intelligent Systems, page , November, 1990.

16

Ranganathan, N. and Shah, M. A vlsi architecture for computing scale space. Computer Vision, Graphics, and Image Processing, 43:178-204, 1988.

17

Rangarajan, K., Allen, Bill, and Shah, M. . Matching motion trajectories. Pattern Recognition, 26:595-610, July, 1993.

18

Rangarajan, K., and Shah, M. Interpretation of motion trajectories using focus of expansion. IEEE PAMI, 14(12):1205-1210, 1992.

19

Rangarajan, K., and Shah, M. Establishing motion correspondence. CVGIP:Image Understanding, pages 56-73, July, 1991.

20

Rangarajan, K., Shah, M. and Van Brackle D. Optimal corner detector. Computer Vision, Graphics, and Image processing, 48:230-245, 1989.

21

Segen, J. Gest: A learning computer vision system that recognizes hand gestures. Machine Learning IV, 1994.

22

Shah, M and Jain, R. Detecting time-varying corners. Computer Vision, Graphics, and Image Processing, 28:345-355, December, 1984.

23

Shah, M. and Sood, A. and Jain, R. Pulse and staircase edge models. Computer Vision, Graphics, and Image Processing, 34:321-341, June, 1986.

24

Shah, M., Rangarajan, K., and Tsai, P. Motion trajectories. IEEE SMC, 23(4):1138-1150, August, 1993.

25

Tian, T.Y., Shah, M. Estimating 3d motion and shape of multiple objects using hough transform. In Proceedings of International Conference on Pattern Recognition, 1994.

26

Tian, T.Y., Shah, M. A general approach for determining 3d motion and structure of multiple objects from image trajectories. In Proceedings of IEEE Workshop on Motion of Nonrigid & Articulate Object, 1994.

27

Tian, T.Y., Shah, M. Motion estimation and segmentation. In Proceedings International Conference on Image Processing, 1994.

28

Tsai, P., and Shah, M. Shape from shading using linear approximation. Image and Vision Computing, (in press).

29

Tsai, P-S, and Shah, M. . A fast linear shape form shading. In IEEE Conference on Computer Vision and Pattern Recognition, pages 734-736, June, 1992.

30

Tsai, Ping-Sing, Keiter, K., Kasparis, T., and Shah, M. Cyclic motion detection. Pattern Recognition, (to appear).

31

Williams, D. and Shah, M. Greedy algorithm for active contour and curvature estimation. Computer Vision, Graphics, and Image Processing, pages 14-26, January, 1992.

32

Williams, D. and Shah, M. Edge characterization using normalized edge detector. Computer Vision, Graphics, and Image Processing: Graphical Models and Image Processing, 55:311-318, July, 1993.

33

Williams, D. and Shah, M. Edge contours using multiple scales. Computer Vision, Graphics, and Image Processing, 51:256-274, September, 1990.

34

R. Zhang, P. S. Tsai, and M. Shah. Shape from photomotion. IEEE CVPR, 1993.

35

Zhang, R., and Shah, M. Height recovery from intensity gradient. In IEEE Conference on Computer Vision and Pattern Recognition, 1994.

36

Zhang, R., Tsai, P., Cryer, J., and Shah, M. Analysis of shape from shading techniques. In IEEE Conference on Computer Vision and Pattern Recognition, 1994.

37

Gould, K., Rangarajan, K., and Shah, M. Detection and representation of events in motion trajectories. In Y. Mahdavieh and R. Gonzalez, editors, Advances in Image Analysis, page . SPIE Optical Engineering Press, 1992.

38

Kaiser, B.J., Bowyer, K.W. and Goldgof, D.B. 1991. On exploring the definition of a range image aspect graph, Proceedings of the 7-th Scandinavian Conference on Image Analysis, Aalborg, Denmark (August 1991), 652-658.

39

Altfeld, J. Jones, J. and Bowyer, K.W. Comparing A*/branch-and-bound parallel algorithms for use in path planning on an Intel hypercube, Florida Artificial Intelligence Research Symposium, Cocoa Beach, Florida (April 1991), 111-115.

40

Wilkins, B., Goldgof, D. and Bowyer, K.W. Toward computing the aspect graph of deformable generalized cylinders, SPIE #1468: Applications of Artificial Intelligence IX, Orlando, Florida (April 1991), 662-673.

41

Ranganathan, N. and Shah, M. A vlsi architecture for computing scale space. Computer Vision, Graphics, and Image Processing, 43:178-204, 1988.

42

Rangarajan, K., and Shah, M. Interpretation of motion trajectories using focus of expansion. IEEE PAMI, Vol. 14, No. 12, pp 205-210, 1992.

43

Function-based recognition for multiple object categories, Image Understanding 59 (1), 1-21, (January 1994).

44

Stark, L., and Bowyer, K.W. Achieving generalized object recognition through reasoning about association of function to structure, IEEE Transactions on Pattern Analysis and Machine Intelligence 13 (10), 1097-1104, (October 1991).

45

Woods, K.S., Doss, C.C., Bowyer, K.W., Clarke, L.P. and Clark, R.A. A neural network approach to microcalcification detection, IEEE 1992 Nuclear Science Symposium and Medical Imaging Conference, Orlando, Florida (October 1992), 1273-1275.

46

Sallam, M., Hubiak, G., Bowyer, K. and Clarke, L. Screening mammogram images for abnormalities developing over time, IEEE 1992 Nuclear Science Symposium and Medical Imaging Conference, Orlando, Florida (October 1992), 1270-1272.

47

Woods, Kevin S., Solka, Jeffry L., Priebe, Carey E., W. Philip Kegelmeyer, Jr. Doss, Christopher C. and Bowyer, Kevin W. Comparative evaluation of pattern recognition techniques for detection of microcalcifications in mammography, International Journal of Pattern Recognition and Artificial Intelligence 7 (6), 1417-1436, (December 1993).

48

Bruno, B., Bennett, N., Bowyer, K., Goldgof, D. and Stark, L. Modeling of Articulated Objects for Machine Perception, Florida Artificial Intelligence Research Symposium, Palm Beach, Florida (April 1992), 247-251.

49

Sutton, M., Stark, L. and Bowyer, K.W. Capturing Function in a Generic Representation Scheme, Eighth Israeli Symposium on Artificial Intelligence and Computer Vision, Ramat Gan, Israel (December 1991), 97-111.

50

Sutton, M., Stark, L. and Bowyer, K.W. What is a "Generic" Object Model for Computer Vision?, Florida Artificial Intelligence Research Symposium, Palm Beach, Florida (April 1992), 252-256.

51

Sutton, M., Stark, L. and Bowyer, K. Reasoning about function to achieve generic recognition of rigid 3-D shapes, accepted to appear in Pattern Recognition.

52

Sutton, M., Stark, L. and Bowyer, K.W. Function-based generic recognition for multiple object categories, in Three-dimensional Object Recognition Systems, A.K. Jain and P.J. Flynn, editors, Elsevier Science Publishers, 447-470, 1993.

53

Eggert, D.W., Bowyer, K.W., Dyer, C.R., Christensen, H.I. and Goldgof, D.B. The scale space aspect graph, IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (11), 1114-1130, (November 1993).

54

Stark, L., Hall, L.O. and Bowyer, K.W. An investigation of methods of combining functional evidence for 3-D object recognition, International Journal of Pattern Recognition and Artificial Intelligence 7 (3), 573-594, (June 1993).

55

Bowyer, K.W., Sallam, M., Eggert, D. and Stewman, J.H. Computing the generalized aspect graph for objects with moving parts, IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (6), 605-610, (June 1993).

56

Eggert, D. and Bowyer, K.W. Computing the perspective projection aspect graph of solids of revolution, IEEE Transactions on Pattern Analysis and Machine Intelligence 15 (2), 109-128, (February 1993).

57

O. Faugeras, J. Mundy, N. Ahuja, C. Dyer, A. Pentland, R. Jain, K. Ikeuchi and Bowyer, K.W. Workshop panel report: Why aspect graphs are not (yet) practical for computer vision, Image Understanding 55 (2), 212-218, (March 1992).

58

Bowyer, K.W. and Astley, S. (editors). State of the Art in Mammographic Image Analysis, World Scientific, 1994.

59

Christensen, H.I., Bowyer, K.W. and Bunke, H. (editors). Active Robot Vision, World Scientific, 1993.

60

Woods, K., Cook, D., Hall, L., Stark, L. and Bowyer, K.W. Learning fuzzy membership functions in a function-based object recognition system, to appear in Lecture Notes in Artificial Intelligence, A. Ralescu, editor, Springer-Verlag.

61

Bowyer, K.W. and Dyer, C.R. Three-Dimensional Shape Representation, in Handbook of Pattern Recognition and Computer Vision, Volume 2: Computer Vision T.Y. Young, editor, Academic Press, 17-51, 1994.

62

Bowyer, K.W., Eggert, D., Stewman, J., and Stark, L. Developing the aspect graph representation for use in image understanding, in Selected Papers on Model-Based Vision (Milestone Series # 72), Hatem Nasr, editor, SPIE Press, 198-216, 1993. (Reprinted from the proceedings of the 1989 DARPA Image Understanding Workshop.)

63

Stark, L. and Bowyer, K.W. Function-based object recognition for multiple object categories, in Advances in Syntactic and Structural Pattern Recognition, H. Bunke, editor, World Scientific Publishing, 441-450, 1992.

64

Eggert, D.W., Bowyer, K.W., Dyer, C.R., Christensen, H.I. and Goldgof, D.B. Applying the scale space concept to perspective projection aspect graphs, in Theory and Applications of Image Analysis: Selected Papers from the 7th Scandinavian Conference on Image Analysis, P. Johansen and S. Olsen, editors, World Scientific Publishing, 48-62, 1992.

65

Hoover, A., Jean-Baptiste, G., Goldgof, D. and Bowyer, K.W. A methodology for evaluating range image segmentation techniques, 1994 IEEE Workshop on Applications of Computer Vision, Sarasota, Florida (December 1994).

66

Green, K., Eggert, D. Stark, L. and Bowyer, K. Generic recognition of articulated objects by reasoning about functionality, 1994 IAPR International Conference on Pattern Recognition, Jerusalem, Israel (October 1994).

67

Green, K., Eggert, D. Stark, L. and Bowyer, K. Generic recognition of articulated objects by reasoning about functionality, 1994 AAAI Workshop on Representing and Reasoning about Device Function, Seattle, Washington (August 1994), 56-64.

68

Woods, K.S. and Bowyer, K.W. Computer detection of stellate lesions, Second International Workshop on Digital Mammography, York, United Kingdom (July 1994).

69

Woods, K.S. and Bowyer, K.W. Generating ROC curves for artificial neural netwoorks, Second International Workshop on Digital Mammography, York, United Kingdom (July 1994).

70

Simpson, K.M. and Bowyer, K.W. Comparison of spatial noise removal techniques for digital mammography, Second International Workshop on Digital Mammography, York, United Kingdom (July 1994).

71

Sallam, M.Y. and Bowyer, K.W. Registering time sequences of mammograms using a 2-D unwarping technique, Second International Workshop on Digital Mammography, York, United Kingdom (July 1994).

72

Woods, K.S. and Bowyer, K.W. Generating ROC curves for artificial neural netwoorks, Seventh Annual IEEE Symposium on Computer-Based Medical Systems, (June 1994), 201-206.

73

Solka, J.L., Poston, W.L., Priebe, C.E., Rogers, G.W., Lorey, R.A., Marchette, D.J., Woods, K.S. and Bowyer, K.W. The detection of micro-calcifications in mammographic images using high dimensional features, Seventh Annual IEEE Symposium on Computer-Based Medical Systems, (June 1994), 139-145.

74

Hoover, A., Goldgof, D. and Bowyer, K.W. Building a B-rep from a segmented range image, IEEE Second CAD-Based Vision Workshop, Champion, Pennsylvania (February 1994), 74-81.

75

Eggert, D., Goldgof, D. and Bowyer, K.W. Reconstructing CAD Models of Articulated Objects, IEEE Second CAD-Based Vision Workshop, Champion, Pennsylvania (February 1994), 98-105.

76

Cook, D.J., Woods, K., Hall, L.O., Stark, L. and Bowyer, K.W. Learning and combining fuzzy values for object recognition, AAAI Fall Symposium: Machine Learning in Computer Vision, Research Triangle Park, North Carolina (October 1993), 139-143.

77

Eggert, D.W., Bowyer, K.W., Dyer, C.R. Aspect graphs: state-of-the-art and applications in digital photogrammetry, ISPRS 27-th Congress: International Archives of Photogrammetry and Remote Sensing, Part B5, Washington, D.C. (August, 1992), 633-645 (invited paper).