Object Detection in the Image using Matlab
Abstract
In videoconferencing, the image quality is significantly affected by the illumination condition.
Unsatisfactory illumination conditions may lead to underexposure or overexposure of the area of
interest, in particular a human face. To resolve this issue, we propose a solution to automatically
improve image quality by correcting exposure and enhancing contrast. Our work is characterized by a
method for automatically building a skin-color model and a novel contrast enhancement approach.
Some techniqu an reduce the computational cost are also introduced. Experimental results show that
obvious improvement in image quality is achieved while the computation overhead is very small. The
proposed solution can be integrated into videoconferencing systems and is especially suitable for
scenarios where low-complexity computing is required. From our experiments, it is found that there is
an optimal resolution to balance between speed and accuracy, while we show in our experiments that
the resolution has apparent influence on both the accuracy and the computing time.
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IEEE International Conference on Intelligent Autonomous Systems, pp. 206–215. Pittsburgh,
PA, Feb. (1993)
2. Atev, S., Masoud, O., Papanikolopoulos, N.: Practical mixtures of Gaussians with ightness
monitoring. In: Proceedings of the IEEE International Conference on Intelligent ransportation
Systems (2004)
3. Azarbayejani, A., Pentland, A.: Real-time self-calibrating stereo person tracking using 3D
shape estimation from blob features. In: Proceedings of the IEEE International Conference on
Pattern Recognition (1996)
4. Ben-Arie, J., Wang, Z., Pandit, P., Rajaram, S.: Human activity recognition using
multidimensional indexing. IEEE Trans. Pattern Anal. Mach. Intell. 24(8), 1091–1104, August
(2002)
5. Beymer, D., Konolige, K.: Real-time tracking of multiple people using continuous detection.
In: International Conference on Computer Vision (1999)
6. Bodor, R.: Multi-camera human activity recognition in unconstrained indoor and outdoor
environments. Ph.D. thesis, University of Minnesota, August (2005)
7. Bodor, R., Drenner, A., Janssen, M., Schrater, P., Papanikolopoulos, N.: Mobile camera
positioning to optimize the observability of human activity recognition tasks. In: Proceedings
of the IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton,
Canada, Aug. (2005)
8. Bodor, R., Jackson, B., Masoud, O., Papanikolopoulos, N.: Image-based reconstruction for
view-independent human motion recognition. In: Proceedings of the IEEE/RSJ International
Conference on Intelligent Robots and Systems, Oct. (2003)
9. Bodor, R., Jackson, B., Papanikolopoulos, N.: Vision-based human tracking and activity
recognition. In: Proceedings of the 11thMediterranean Conference on Control and Automation,
June (2003)
10. Bregler, C.: Learning and recognizing human dynamics in video sequences. In: Proceedings of
the IEEE Conference on Computer Vision and Pattern Recognition (1997)
11. Cao, D.,Masoud, O., Boley, D., Papanikolopoulos, N.: Onlinemotion classification using
support vector machines. In: IEEE International Conference on Robotics and Automation, Apr.
(2004)
12. Chen, X., Davis, J.: Camera placement considering occlusion for robust motion capture.
Technical Report CS-TR-2000-07, Stanford University (2000)
13. Collins, R., Amidi, O., Kanade, T.: An active camera system for acquiring multi-view video.
In: Proceedings of the 2002 International Conference on Image Processing, Sept. (2002)
14. Cretual, A., Chaumette, F., Bouthemy, P.: Complex object tracking by visual servoing based
on 2D image motion. In: Proceedings of the IAPR International Conference on Pattern
Recognition, Australia, Aug. (1998)
15. Cutler, R., Turk, M.: View-based interpretation of real-time optical flow for gesture
recognition. In: Proceedings of the Third IEEE Conference on Face and Gesture Recognition.
Nara, Japan, Apr. (1998)
16. Daniilidis, K., Krauss, C., Hansen, M., Sommer, G.: Real-time tracking of moving objects with
an active camera. Real-Time Imaging 4, 3–20 (1998)
17. Darrell, T., Gordon, G., Harville,M., Woodfill, J.: Integrated person tracking using stereo,
color, and pattern detection. Int. J. Comput. Vis. 37(2), 175–185, June (2000)
18. Davis, J., Chen, X.: Calibrating pan-tilt cameras in wide-area surveillance networks. In:
Proceedings of the IEEE International Conference on Computer Vision (2003)
19. Denzler, J., Zobel, M., Niemann, H.: On optimal camera parameter selection in Kalman filter
based object tracking. In: Proceedings of the 24th DAGM Symposium on Pattern Recognition,
pp. 17–25. Zurich, Switzerland (2002)
20. Efros, A., Berg, A., Mori, G., Malik, J.: Recognizing action at a distance. In: Proceedings of
the IEEE Conference on Computer Vision (2003)
21. Elgammal, A., Duraiswami, R., Harwood, D., Davis, L.: Background and foreground modeling
using nonparametric kernel density estimation for visual surveillance. Proc. IEEE 90, 1151–
1163 (2002)
22. Eveland, C., Konolige, K., Boles, R.: Background modeling for segmentation of video- rate
stereo sequences. In: Proceedings of the IEEE Conference on Computer Vision and Pattern
Recognition. Santa Barbara, CA (1998)
23. Fablet, R., Black, M.J.: Automatic detection and tracking of human motion with a view- based
representation. In: European Conference on Computer Vision, May (2002)
24. Fleishman, S., Cohen-Or, D., Lischinski, D.: Automatic camera placement for image- based
modeling. In: Proceedings of Pacific Graphics, vol. 99, pp. 12–20 (1999)
25. Gasser, G., Bird, N.,Masoud, O., Papanikolopoulos, N.: Human activity monitoring at bus
stops. In: Proceedings of the IEEE Conference on Robotics and Automation (2004)
26. Gerkey, B., Vaughan, R.T., Howard, A.: The player/stage project: tools for multi-robot and
distributed sensor systems. In: Proceedings of the 11th International Conference on Advanced
Robotics, pp. 317–323. Coimbra, Portugal, June (2003)
27. Grimson, W., Stauffer, C., Romano, R., Lee, L.: Using adaptive tracking to classify and
monitor activities in a site. In: Proceedings of the International Conference on Computer
Visiona and Pattern Recognition, June (1998)
28. Haritaoglu, I., Harwood, D., Davis, L.: W4: real-time surveillance of people and their activities.
IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 809–830 (2000)
29. Heisele, B., Verri, A., Poggio, T.: Learning and vision machines. Proc. IEEE 90(7), 1164–1177
(2002)
30. Hodgins, J., O’Brien, J., Tumblin, J.: Do geometric models affect judgements of human
motion? In: Proceedings of the Graphics Interface Conference. Canada, May (1997)
31. Isler, V., Kannan, S., Daniilidis, K.: Vc-dimension of exterior visibility. IEEE Trans. Pattern
Anal. Mach. Intell. 26(5), 667–671 (2004)
32. Lin, C., Wang, C., Chang, Y., Chen, Y.: Real-time object extraction and tracking with an active
camera using image mosaics. In: Proceedings of the IEEE International Workshop on
Multimedia Signal Processing, Dec. (2002)
33. Lyons, D.: Discrete event modeling of misrecognition in PTZ tracking. In: Proceedings of the
IEEE Conference on Advanced Video and Signal Based Surveillance. Miami, FL, July (2003)
34. Masoud, O., Papanikolopoulos, N.P.: A method for human action recognition. Image Vis.
Comput. 21(8), 729–743 (2003)
35. Masoud, O., Papanikolopoulos, N.P.: Using geometric primitives to calibrate traffic scenes. In:
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.
Japan, Oct. (2004)
36. Maurin, B., Masoud, O., Papanikolopoulos, N.: Monitoring crowded traffic scenes. In:
Proceedings of the IEEE International Conference on Intelligent Transportation Systems.
Singapore, Sept. (2002)
37. McKenna, S., Jabri, S., Duric, Z., Wechsler, H.: Tracking interacting people. In: Proceedings
of the Conference on Automatic Face and Gesture Recognition. Grenoble, France, Mar. (2000)
38. Mittal, A., Huttenlocher, D.: Scene modeling for wide area surveillance and image synthesis.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. South
Carolina, June (2000)
39. Mori, H., Charkari, M., Matsushita, T.: On-line vehicle and pedestrian detections based on sign
pattern. IEEE Trans. Ind. Electron. 41(4), 384–391 (1994)
40. Murray, D., Basu, A.: Motion tracking with an active camera. IEEE Trans. Pattern Anal. Mach.
Intell. 16(5), 449–459 (1994) Volume – 1, Issue – 1, August 2012.
Al-Qalam Journal of Pure Sciences; A Periodical Open Access Scientific Journal