基于序列图像的人头定位
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摘要
基于序列图像的人头定位是基于银行大厅或重要的室内场所的自动监控和报警系统提出来的，旨在实现视频监控的智能化。视频监控系统作为一种可视化监控手段在公共安全领域得到了广泛的应用。本文旨在采用摄像机连续的采集监控场景的图像，通过计算机的检测和识别尽早发现不法人员(比如蒙面，太阳帽遮挡，佩戴口罩等五官不全者)入侵，并根据系统的设定，自动向异地的监控中心报警。
本文利用图像序列中所蕴含的运动信息，依据所研究人脸由于遮蔽可能不完整的特点对基于序列图像的人头定位进行了研究。
第一，本文研究了背景生成和更新技术，系统地分析和比较了背景生成和更新算法，提出了一种分组更新的背景生成算法；并给出了多高斯分布模型的背景更新新算法。第二，本文给出了利用最近三帧图像检测当前图像中运动目标轮廓的算法，利用沈俊边缘检测算子和线段光滑度指标，对检测到的目标进行过滤，并消除干扰。第三，本文根据人头的特征实现了基于头颈部凹点的人头定位，提出了圆环人头定位的Hough变换算法，完成了人头和人脸的定位；最后给出了实验数据及分析。
Human head location based on image sequence is brought forward by the automatic surveillance and alarm system that is applied in the halls of banks or import indoor places. It aims at endowing the video surveillance system with intelligence. The video surveillance system, as a visible surveillance approach, is widely employed in the public security field. In this paper, the system continuously captures the images of the monitored scene by a camera, perceives the invasion of irregular people with a mask on its face, a respirator on its mouth or a cap on its head and so on by the detection and recognition of the computer as early as possible and automatically alarms the remote control center according to the setting of the system.
In this paper, we research the human head location based on image sequence according to the dynamic information of moving objects in a image sequence and the fact that some of organs on the face are perhaps not present when the face is covered.
First, this paper investigates the background generation and update technology, systematically analyzes and contrasts the algorithms of the technology, then presents a new group-update background generation algorithm and an improved multiple Gaussian model background generation algorithm. Second, we propose a contour detection method by which we can detect moving objects in the current image according to the three latest images. Then we apply the Shen Jun Operator and the smooth criteria of lines to eliminate interference from the detected target. Third, This paper introduces a head location approach according to the characteristic points at people's neck and presents a new cirque-based Hough transform for locating human head. Finally, the experimental results and analysis are presented.
本文利用图像序列中所蕴含的运动信息，依据所研究人脸由于遮蔽可能不完整的特点对基于序列图像的人头定位进行了研究。
第一，本文研究了背景生成和更新技术，系统地分析和比较了背景生成和更新算法，提出了一种分组更新的背景生成算法；并给出了多高斯分布模型的背景更新新算法。第二，本文给出了利用最近三帧图像检测当前图像中运动目标轮廓的算法，利用沈俊边缘检测算子和线段光滑度指标，对检测到的目标进行过滤，并消除干扰。第三，本文根据人头的特征实现了基于头颈部凹点的人头定位，提出了圆环人头定位的Hough变换算法，完成了人头和人脸的定位；最后给出了实验数据及分析。
Human head location based on image sequence is brought forward by the automatic surveillance and alarm system that is applied in the halls of banks or import indoor places. It aims at endowing the video surveillance system with intelligence. The video surveillance system, as a visible surveillance approach, is widely employed in the public security field. In this paper, the system continuously captures the images of the monitored scene by a camera, perceives the invasion of irregular people with a mask on its face, a respirator on its mouth or a cap on its head and so on by the detection and recognition of the computer as early as possible and automatically alarms the remote control center according to the setting of the system.
In this paper, we research the human head location based on image sequence according to the dynamic information of moving objects in a image sequence and the fact that some of organs on the face are perhaps not present when the face is covered.
First, this paper investigates the background generation and update technology, systematically analyzes and contrasts the algorithms of the technology, then presents a new group-update background generation algorithm and an improved multiple Gaussian model background generation algorithm. Second, we propose a contour detection method by which we can detect moving objects in the current image according to the three latest images. Then we apply the Shen Jun Operator and the smooth criteria of lines to eliminate interference from the detected target. Third, This paper introduces a head location approach according to the characteristic points at people's neck and presents a new cirque-based Hough transform for locating human head. Finally, the experimental results and analysis are presented.
引文
1．王新余，张桂林．基于光流的运动目标实时检测方法研究．计算机工程与应用．2004，1：43-46
2．周小高，朱秋煜，俞人杰，朱繁源．基于差值图像及肤色特征的人脸定位方法．上海大学学报(自然科学版)，2003，9(1)：5-8
3．林洪文，涂丹，李国辉等．基于减背景技术的运动目标检测方法研究．国防科技大学学报，2003，25(3)：66-69
4．伏思华，张小虎．基于序列图像的运动目标实时检测方法．光学技术．2004，30(2)：215-222
5．潘锦辉，廖庆敏，林行刚．视频序列中运动目标的自动提取．清华大学学报(自然科学版)，2001，41(4/5)：190-193
6．徐一华，朱玉文，贾云得．一种人头部实时跟踪方法．中国图像图形学报，2002，7(A)，1：11-15
7. Antonio C, Ricardo L, Huang T S. 3D model-based head tracking [J]. In: proc. of SPIE on VCIP [C] , San Jose, CA, 1997, 3024: 426-434
8. Antonio C, Brendan F, Huang T S. Detection and tracking of faces and facial features [A]. In: Proc. IEEE on ICIP [C]. Kobe, Japan, 1999: 657-661
9. Marco Cascia, John Isidoro, Stan Sclaroff. Head tracking via robust registration in texture map images [A]. In: Proc. IEEE on CVPR [C]. Santa Barbara, CA, 1998:508-514
10. Jie Yang, Alex Waibel. Tracking human faces in real-time [R]. CMU CS Technical Report, CMU-CS-95-210, 1995
11. Nuria Oliver, Alex Pentland, Francois Berard. LAFTER: Lips and face real time tracker with facial expression recognition [A]. In: Proc. IEEE on CVPR [C]. San Juan, Puerto Rico, 1997: 123-129
12. Jianbo Shi, Carlo Tomasio Good features to track [A]. In: Proc. IEEE on CVPR [C]. Seattle, W A, 1994: 593-600
13. Tiziano Tommasini, Andrea Fusiello, Emanuele Trucco et al. Making good features track better [A]. In: Proc. IEEE on CVPR [C]. Santa Barbara, C A, 1998: 178-183
14. Cordea M D, Petriu E M, Georganas N D et al. Real-time 21/2D head pose recovery for model-based video-coding [A]. In: Proc. IEEE on Instrumentation and Measurement Technology [C]. Baltimore, M D, 2000: 601-606
15. Haritaoglu I, Flickner M. Detection and tracking of shopping groups in stores, proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, USA, 2001 Page(s): Ⅰ-431-Ⅰ-438 vol. 1
16. Crowley J L, Berard F. Multi-modal tracking of faces for video communications [A]. In: Proc. IEEE on CVPR [C]. San Juan, Puerto Rico, 1997: 640-645
17. Jepson A D, Fleet D J, El-Maraghi T R. Robust online appearance models for visual tracking proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, USA, 2001 Page(s): Ⅰ-415-Ⅰ-422 vol.1
18. Yang M H, Kriegman D, Ahuja N. Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24 (1): 34-58
19. Hashimoto R F, Barrera J. A note on Park and Chin's algorithm [structuring element decomposition]. IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 24, Issue: 1, Year: Jan 2002, Page(s): 139-144
20. Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, Volume: 2, 23-25 June 1999, Pages: 252, Vol. 2
21. Viola P, Jones M. Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001. Volume: 1, Year: 2001, Page(s): Ⅰ-511-Ⅰ-518 vol. 1
22. Hjelms, Erik, Low, Boon Kee. Face Detection: A Survey. Computer Vision and Image Understanding Volume: 83, Issue: 3, September, 2001, pp. 236-274
23. Yow, Kin Choong, Cipolla, Roberto. Feature-based human face detection. Image and Vision Computing Volume: 15, Issue: 9, September, 1997, pp. 713-735
24. Fathy M, Siyal M Y. An image detection technique based on morphological edge detection and background differencing for real-time traffic analysis. Pattern Recognition Letters 16, 1995: 1321-1330
25. Yang G Z, Huang T S. Human face detection in a complex background. Pattern Recognition, 1994, 27(1): 53—63
26．王栓，艾海舟，何克忠．基于差分图像的多运动目标的检测和跟踪．中国图像图形学报，1999，4(6)：470-474
27．艾海舟，王栓，何克忠．基于差分图象的人脸检测．中国图像图形学报，1998，3(12)：987-992
28．杜奇，向健勇，袁胜春．一种改进的最大类间方差法．红外技术．2003，25(5)：33-36
29. Christopher Richard Wren, Ali Azarbayejani, Trevor Darrell, Alex Paul Pentland. Pfinder: RealTime Tracking of the Human Body. IEEE Trans. Pattern Analysis And Machine Intelligence. 1997, 19(7): 780-785
30. Vieren C, Cabestaing F, Postaire J. Catching Moving Objects with Snakes for Motion Tracking. Pattern Recognition Letters, 16, 1995, 679-685
31. Mingwu Ren, Jingyu Yang, Han Sun. Tracing boundary contours in a binary image. Image and Vision Computing. 2002, 20(2): 125-131
32. Yiwu Lei, Kok Cheong Wong. Ellipse detection based on symmetry. Pattern Recognition Letters, 20 (1999): 41-47
33. Christian Daul, Pierre Graebling, Ernest Hirsch. From the Hough Transform to a New Approach for the Detection and Approximation of Elliptical Arcs. Computer Vision and Image understanding, Vol. 72, No. 3, December, pp. 215-236, 1998
34. Peng-Yeng Yin. A new circle/ellipse detector using genetic algorithms. Pattern Recognition Letters, 1999, 20 (7): 731-740
35. P.S.Nair, A.T.Saunders, Jr. Hough transform based ellipse detection algorithm. Pattern Recognition Letters, 1996,17 (7): 777-784
36. Ren Mingwu, Yang Jingyu, Sun Han. An improved Contour Tracing Algorithm: Connectivity Preserving, Fast Speed and Correct Always, 《Proceeding of the Ninth AJOU-FIT-NUST Seminar》, November 3-4, 2000, pp135-142
37. Cucchiara R, Grana C, Piccardi M, Prati A. Detecting objects, shadows and ghosts in video streams by exploiting color and motion information. Image Analysis and Processing, 2001. Proceedings. 11th International Conference on, 26-28 Sept. 2001, Pages: 360-365
38. Cucchiara R, Grana C, Piccardi M, Prati A. Statistic and knowledge-based moving object detection in traffic scenes. Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE, 1-3 Oct. 2000, Pages: 27-32
39. Ying Ren, Chin-Seng Chua, Yeong-Khing Ho. Motion detection with non-stationary background. Image Analysis and Processing, 2001. Proceedings. 11th International Conference on, 26-28 Sept. 2001, Pages: 78-83
40. Izquierdo D, Berthoumieu Y. Region level segmentation based on a derivative approach for video tracking process. Image Processing. 2002. Proceedings. 2002 International Conference on, Volume: 2, 22-25 Sept. 2002, Pages: Ⅱ-321-Ⅱ-324
41．夏德深，傅德胜．现代图像处理技术与应用．东南大学出版社，1997
42．徐建华．图像处理与分析．科学出版社，1992
2．周小高，朱秋煜，俞人杰，朱繁源．基于差值图像及肤色特征的人脸定位方法．上海大学学报(自然科学版)，2003，9(1)：5-8
3．林洪文，涂丹，李国辉等．基于减背景技术的运动目标检测方法研究．国防科技大学学报，2003，25(3)：66-69
4．伏思华，张小虎．基于序列图像的运动目标实时检测方法．光学技术．2004，30(2)：215-222
5．潘锦辉，廖庆敏，林行刚．视频序列中运动目标的自动提取．清华大学学报(自然科学版)，2001，41(4/5)：190-193
6．徐一华，朱玉文，贾云得．一种人头部实时跟踪方法．中国图像图形学报，2002，7(A)，1：11-15
7. Antonio C, Ricardo L, Huang T S. 3D model-based head tracking [J]. In: proc. of SPIE on VCIP [C] , San Jose, CA, 1997, 3024: 426-434
8. Antonio C, Brendan F, Huang T S. Detection and tracking of faces and facial features [A]. In: Proc. IEEE on ICIP [C]. Kobe, Japan, 1999: 657-661
9. Marco Cascia, John Isidoro, Stan Sclaroff. Head tracking via robust registration in texture map images [A]. In: Proc. IEEE on CVPR [C]. Santa Barbara, CA, 1998:508-514
10. Jie Yang, Alex Waibel. Tracking human faces in real-time [R]. CMU CS Technical Report, CMU-CS-95-210, 1995
11. Nuria Oliver, Alex Pentland, Francois Berard. LAFTER: Lips and face real time tracker with facial expression recognition [A]. In: Proc. IEEE on CVPR [C]. San Juan, Puerto Rico, 1997: 123-129
12. Jianbo Shi, Carlo Tomasio Good features to track [A]. In: Proc. IEEE on CVPR [C]. Seattle, W A, 1994: 593-600
13. Tiziano Tommasini, Andrea Fusiello, Emanuele Trucco et al. Making good features track better [A]. In: Proc. IEEE on CVPR [C]. Santa Barbara, C A, 1998: 178-183
14. Cordea M D, Petriu E M, Georganas N D et al. Real-time 21/2D head pose recovery for model-based video-coding [A]. In: Proc. IEEE on Instrumentation and Measurement Technology [C]. Baltimore, M D, 2000: 601-606
15. Haritaoglu I, Flickner M. Detection and tracking of shopping groups in stores, proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, USA, 2001 Page(s): Ⅰ-431-Ⅰ-438 vol. 1
16. Crowley J L, Berard F. Multi-modal tracking of faces for video communications [A]. In: Proc. IEEE on CVPR [C]. San Juan, Puerto Rico, 1997: 640-645
17. Jepson A D, Fleet D J, El-Maraghi T R. Robust online appearance models for visual tracking proceedings of IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii, USA, 2001 Page(s): Ⅰ-415-Ⅰ-422 vol.1
18. Yang M H, Kriegman D, Ahuja N. Detecting faces in images: A survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 24 (1): 34-58
19. Hashimoto R F, Barrera J. A note on Park and Chin's algorithm [structuring element decomposition]. IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 24, Issue: 1, Year: Jan 2002, Page(s): 139-144
20. Stauffer C, Grimson W E L. Adaptive background mixture models for real-time tracking. Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, Volume: 2, 23-25 June 1999, Pages: 252, Vol. 2
21. Viola P, Jones M. Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2001. CVPR 2001. Volume: 1, Year: 2001, Page(s): Ⅰ-511-Ⅰ-518 vol. 1
22. Hjelms, Erik, Low, Boon Kee. Face Detection: A Survey. Computer Vision and Image Understanding Volume: 83, Issue: 3, September, 2001, pp. 236-274
23. Yow, Kin Choong, Cipolla, Roberto. Feature-based human face detection. Image and Vision Computing Volume: 15, Issue: 9, September, 1997, pp. 713-735
24. Fathy M, Siyal M Y. An image detection technique based on morphological edge detection and background differencing for real-time traffic analysis. Pattern Recognition Letters 16, 1995: 1321-1330
25. Yang G Z, Huang T S. Human face detection in a complex background. Pattern Recognition, 1994, 27(1): 53—63
26．王栓，艾海舟，何克忠．基于差分图像的多运动目标的检测和跟踪．中国图像图形学报，1999，4(6)：470-474
27．艾海舟，王栓，何克忠．基于差分图象的人脸检测．中国图像图形学报，1998，3(12)：987-992
28．杜奇，向健勇，袁胜春．一种改进的最大类间方差法．红外技术．2003，25(5)：33-36
29. Christopher Richard Wren, Ali Azarbayejani, Trevor Darrell, Alex Paul Pentland. Pfinder: RealTime Tracking of the Human Body. IEEE Trans. Pattern Analysis And Machine Intelligence. 1997, 19(7): 780-785
30. Vieren C, Cabestaing F, Postaire J. Catching Moving Objects with Snakes for Motion Tracking. Pattern Recognition Letters, 16, 1995, 679-685
31. Mingwu Ren, Jingyu Yang, Han Sun. Tracing boundary contours in a binary image. Image and Vision Computing. 2002, 20(2): 125-131
32. Yiwu Lei, Kok Cheong Wong. Ellipse detection based on symmetry. Pattern Recognition Letters, 20 (1999): 41-47
33. Christian Daul, Pierre Graebling, Ernest Hirsch. From the Hough Transform to a New Approach for the Detection and Approximation of Elliptical Arcs. Computer Vision and Image understanding, Vol. 72, No. 3, December, pp. 215-236, 1998
34. Peng-Yeng Yin. A new circle/ellipse detector using genetic algorithms. Pattern Recognition Letters, 1999, 20 (7): 731-740
35. P.S.Nair, A.T.Saunders, Jr. Hough transform based ellipse detection algorithm. Pattern Recognition Letters, 1996,17 (7): 777-784
36. Ren Mingwu, Yang Jingyu, Sun Han. An improved Contour Tracing Algorithm: Connectivity Preserving, Fast Speed and Correct Always, 《Proceeding of the Ninth AJOU-FIT-NUST Seminar》, November 3-4, 2000, pp135-142
37. Cucchiara R, Grana C, Piccardi M, Prati A. Detecting objects, shadows and ghosts in video streams by exploiting color and motion information. Image Analysis and Processing, 2001. Proceedings. 11th International Conference on, 26-28 Sept. 2001, Pages: 360-365
38. Cucchiara R, Grana C, Piccardi M, Prati A. Statistic and knowledge-based moving object detection in traffic scenes. Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE, 1-3 Oct. 2000, Pages: 27-32
39. Ying Ren, Chin-Seng Chua, Yeong-Khing Ho. Motion detection with non-stationary background. Image Analysis and Processing, 2001. Proceedings. 11th International Conference on, 26-28 Sept. 2001, Pages: 78-83
40. Izquierdo D, Berthoumieu Y. Region level segmentation based on a derivative approach for video tracking process. Image Processing. 2002. Proceedings. 2002 International Conference on, Volume: 2, 22-25 Sept. 2002, Pages: Ⅱ-321-Ⅱ-324
41．夏德深，傅德胜．现代图像处理技术与应用．东南大学出版社，1997
42．徐建华．图像处理与分析．科学出版社，1992