Vehicle detection in very high resolution satellite images of city areas

IEEE Transactions on Geoscience and Remote Sensing

Volumn 48, Issue 7, 2010, Pages 2795-2806

  Leitloff, Jens ^a,b   Hinz, Stefan ^a,c   Stilla, Uwe ^a  

^a Institute of Photogrammetry and Cartography   (Germany)

^b GERMAN AEROSPACE CENTER DLR   (Germany)

^c KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

Author keywords

Adaptive boosting (AdaBoost); Parameter estimation; Satellite imagery; Vehicle detection

Indexed keywords

ADABOOST; APRIORI; DETECTION RATES; HAAR-LIKE FEATURES; HIGH RELIABILITY; IMAGE ACQUISITION TIME; IMPLICIT MODELING; LINE EXTRACTION TECHNIQUE; MAIN ROADS; OPTICAL SATELLITE IMAGES; ROAD NETWORK; ROBUST PARAMETER ESTIMATION; STATISTICAL CLASSIFICATION TECHNIQUES; TRAFFIC CONDITIONS; TRAFFIC FLOW; VEHICLE DETECTION; VERY HIGH RESOLUTION SATELLITE IMAGES;

ADAPTIVE BOOSTING; METAL ANALYSIS; MOTOR TRANSPORTATION; ROADS AND STREETS; SATELLITE IMAGERY; SENSORS; TRAFFIC CONTROL; TRAFFIC SURVEYS; VEHICLES;

PARAMETER ESTIMATION;

AUTOMATION; DATA ACQUISITION; DETECTION METHOD; ESTIMATION METHOD; IMAGE ANALYSIS; METROPOLITAN AREA; MOVEMENT; PARAMETERIZATION; ROAD TRANSPORT; SATELLITE IMAGERY; SENSOR; SPATIAL RESOLUTION; TRAFFIC MANAGEMENT; TRANSPORT VEHICLE;

EID: 77953869747     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2043109     Document Type: Article

References (68)

1. U.S. Department of Transportation-Research and Innovative Technology Administration-Bureau of Transportation Statistics, National Transportation Statistics 2008, 2007. accessed on: Aug. 20, 2008. [Online]. Available: http://www.bts.gov/publications/national-transportation- statistics/
2. G. Campell, Office for Official Publications of the European Communities, Panorama of Transport, 2007. [Online]. Available: http:// epp.eurostat.ec. europa.eu/ cache/ITY-OFFPUB/ KS-DA-07-001/EN/KSDA-07-001-EN.PDF
3. S. Hinz and U. Stilla, "Car detection in aerial thermal images by local and global evidence accumulation," Pattern Recognit. Lett., vol.27, no.4, pp. 308-315, Mar. 2006.
4. M. McCord, P. Goel, Z. Jiang, B. Coifman, Y. Yang, and C. J. Merry, "Improving AADT and VDT estimation with high-resolution satellite imagery," presented at the Pecora 15/Land Satellite Inform. IV Symp., Denver, CO, 2002.
5. R. Ruskoné, L. Guiges, S. Airault, and O. Jamet, "Vehicle detection on aerial images: A structural approach," in Proc. 13th Int. Conf. Pattern Recog., G. Kropatsch, Ed., Vienna, Austria, Aug. 1996, vol.3, pp. 900-904.
6. P. Burlina, V. Parameswaran and R. Chellappa, "Sensitivity analysis and learning strategies for context-based vehicle detection algorithms," in Proc. DARPA Image Underst. Workshop, Monterey, CA, 1997, pp. 577-584. [Online]. Available: http://ftp.utcluj.ro/pub/docs/imaging/ Autonomous-driving/ Sensitivit-Learning-ps.ps
7. G. Liu, F. Zhuge, L. Gong, and R. Haralick, "Performance evaluation of the CFAR vehicle detection algorithm," in Proc. DARPA Image Underst. Workshop, Monterey, CA, Nov. 1998, pp. 1229-1234.
8. T. Zhao and R. Nevatia, "Car detection in low resolution aerial images," Image Vis. Comput., vol.21, no.8, pp. 693-703, Aug. 2003.
9. A. Rajagopalan and R. Chellappa, "Higher-order-statistics-based detection of vehicles in still images," J. Opt. Soc. Amer., vol.18, no.12, pp. 3037-3048, Dec. 2001.
10. S. Hinz and A. Baumgartner, "Vehicle detection in aerial images using generic features, grouping and context, in Proc. 23rd DAGM Symp. Pattern Recog., Munich, Germany, vol. 2191, Lecture Notes on Computer Sciene, B. Radig, and S. Florczyk, Eds. Berlin, Germany: Springer-Verlag, 2001, pp. 45-52.
11. H. Moon, R. Chellappa, and A. Rosenfeld, "Performance analysis of a simple vehicle detection algorithm," Image Vis. Comput., vol.20, no.1, pp. 1-13, Jan. 2002.
12. H. Grabner, T. T. Nguyen, B. Gruber, and H. Bischof, "On-line boostingbased car detection from aerial images," ISPRS J. Photogramm. Remote Sens., vol.63, no.3, pp. 382-396, May 2008.
13. C. K. Toth and D. Grejner-Brzezinska, "Extracting dynamic spatial data from airborne imaging sensors to support traffic flow estimation," ISPRS J. Photogramm. Remote Sens., vol. 61, no. 3/4, pp. 137-148, Dec. 2006.
14. W. Yao, S. Hinz, and U. Stilla, "Automatic vehicle extraction from airborne LiDAR data of urban areas using morphological reconstruction," presented at the 5th IAPR Workshop Pattern Recog. Remote Sens., Tampa, FL, 2008.
15. E. Michaelsen and U. Stilla, "Estimating urban activity on high-resolution thermal image sequences aided by large scale vector maps," in Proc. IEEE/ISPRS Joint Workshop Remote Sens. Data Fusion Over Urban Areas, Rome, Italy, Nov. 2001, pp. 25-29.
16. S. Hinz, R. Bamler, and U. Stilla, "Theme issue: Airborne and spaceborne traffic monitoring," ISPRS J. Photogramm. Remote Sens., vol. 61, no. 3/4, pp. 135-136, Dec. 2006.
17. M. Kirchhof and U. Stilla, "Detection of moving objects in airborne thermal videos," ISPRS J. Photogramm. Remote Sens., vol. 61, no. 3/4, pp. 187-196, Dec. 2006.
18. W. Yao, S. Hinz, and U. Stilla, "Automatic analysis of traffic scenario from airborne thermal infrared video," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 37, no. B3A, pp. 223-228, 2008. [Online]. Available: http://www.isprs.org/congresses/beijing2008/proceedings/3- pdf/34.pdf
19. J. Ender, "Space-time processing for multichannel synthetic aperture radar," Electron. Commun. Eng. J., vol.11, no.1, pp. 29-38, Feb. 1999.
20. C. H. Gierull, "Statistical analysis of multilook SAR interferograms for CFAR detection of ground moving targets," IEEE Trans. Geosci. Remote Sens., vol.42, no.4, pp. 691-701, Apr. 2004.
21. D. Cerutti-Maori, J. Klare, A. Brenner, and J. Ender, "Wide-area traffic monitoring with the SAR/GMTI system PAMIR," IEEE Trans. Geosci. Remote Sens., vol.46, no.10, pp. 3019-3030, Oct. 2008.
22. U. Stilla, E. Michaelsen, U. Sörgel, S. Hinz, and J. Ender, "Airborne monitoring of vehicle activity in urban areas," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 35, no. Part B, pp. 973-979, 2004. [Online]. Available: http://www.ipk.bv.tum.de/pub/2004/stilla-et-al- isprs04-pap.pdf
23. F. Meyer, S. Hinz, A. Laika, D. Weihing, and R. Bamler, "Performance analysis of the TerraSAR-X traffic monitoring concept," ISPRS J. Photogramm. Remote Sens., vol. 61, no. 3/4, pp. 225-242, Dec. 2006.
24. S. Suchandt, H. Runge, H. Breit, A. Kotenkov, D. Weihing, and S. Hinz, "Traffic measurement with TerraSAR-X: Processing system overview and first results," in Proc. EUSAR, Friedrichshafen, Germany, 2008, pp. 55-58. [Online]. Available: http://elib.dlr.de/53757/
25. R. Alba-Flores, S. Kuthadi, and F. Rios-Gutiérrez, "Detecting and counting vehicles from high resolution satellite imagery," in Proc. Circuits, Signals, Syst., M. H. Rashid, Ed., Clearwater Beach, FL, 2004, pp. 300-305. [Online]. Available: http://www.actapress.com/PaperInfo.aspx?PaperID= 18429
26. M. McCord, C. Merry, and P. Goel, "Incorporating satellite imagery in traffic monitoring programs," in Proc. North Amer. Travel Monit. Exhib. Conf., Charlotte, NC, 1998. [Online]. Available: http://www.fhwa.dot. gov/ohim/tvtw/natmec/00004.pdf
27. G. Sharma, C. J. Merry, P. Goel, and M. McCord, "Vehicle detection in 1-m resolution satellite and airborne imagery," Int. J. Remote Sens., vol.27, no.4, pp. 779-797, Feb. 2006.
28. A. Gerhardinger, D. Ehrlich, and M. Pesaresi, "Vehicle detection from very high resolution satellite imagery," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 36, no. Part 3/W24, pp. 83-88, 2005.
29. X. Jin and C. H. Davis, "Vehicle detection from high-resolution satellite imagery using morphological shared-weight neural networks," Image Vis. Comput., vol.25, no.9, pp. 1422-1431, Sep. 2007.
30. H. Zheng, L. Pan, and L. Li, "A morphological neural network approach for vehicle detection from high resolution satellite imagery," in Proc. Int. Conf. Neural Inform. Process., vol.4233, Lecture Notes in Computer Science, I. King, J. Wang, L. Chan, and D. L. Wang, Eds. New York: Springer-Verlag, 2006, pp. 99-106. (Pubitemid 44699714)
31. N. Otsu, "A threshold selection method from gray-level histograms," IEEE Trans. Syst.,Man, Cybern., vol.SMC-9, no.1, pp. 62-66, Jan. 1979.
32. H. Zheng and L. Li, "An artificial immune approach for vehicle detection from high resolution space imagery," Int. J. Comput. Sci. Netw. Secur., vol.7, no.2, pp. 67-72, Feb. 2007. [Online]. Available: http:// paper.ijcsns.org/07-book/200702/200702A10.pdf
33. Y. Zhang and Z. Xiong, "Moving vehicle detection using a single set of QuickBird imagery-An initial study," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol.36, no.7, pp. 397-402, 2006. [Online]. Available: http://www.itc.nl/isprsc7/symposium/proceedings/ TS17-1.pdf
34. M. Pesaresi, K. H. Gutjahr, and E. Pagot, "Estimating the velocity and direction of moving targets using a single optical VHR satellite sensor image," Int. J. Remote Sens., vol.29, no.4, pp. 1221-1228, Feb. 2008.
35. J. Leitloff, S. Hinz, and U. Stilla, "Inferring traffic activity from optical satellite image," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 36, no. 3/W49B, pp. 89-94, 2007. [Online]. Available: http:// www.pf.bv.tum.de/isprs/pia07/pubb/PIA07-Leitloff-et-al.pdf
36. C.-C. Chen, C. A. Knoblock, C. Shahabi, Y.-Y. Chiang, and S. Thakkar, "Automatically and accurately conflating orthoimagery and street maps," in Proc. 12th Annu. ACM Int. Workshop GIS, Washington, DC, 2004, pp. 47-56.
37. Z. Yu, V. Prinet, C. Pan, and P. Chen, "A novel two-steps strategy for automatic GIS-image registration," in Proc. ICIP, 2004, vol.3, pp. 1711-1714.
38. X. Wu, R. Carceroni, H. Fang, S. Zelinka, and A. Kirmse, "Automatic alignment of large-scale aerial rasters to road-maps," in Proc. 15th Annu. ACM Int. Symp. Adv. GIS, Seattle, WA, 2007, pp. 1-8.
39. QuickBird Imagery Product-Product Guide, revision 5.0 ed, Digital-Globe, Inc., Longmont, CO, Mar. 2009.
40. J. Friedman, T. Hastie, and R. Tibshirani, "Additive logistic regression: A statistical view of boosting," Ann. Stat., vol.28, no.2, pp. 337-407, 2000.
41. Y. Freund and R. E. Schapire, "A decision-theoretic generalization of online learning and an application to boosting," J. Comput. Syst. Sci., vol.55, no.1, pp. 119-139, Aug. 1997. [Online]. Available: http://dx.doi.org/ 10.1006/jcss.1997.1504
42. R. E. Schapire and Y. Singer, "Improved boosting algorithms using confidence-rated predictions," Mach. Learn., vol.37, no.3, pp. 297-336, Dec. 1999.
43. R. Lienhart, A. Kuranov, and V. Pisarevsky, "Empirical analysis of detection cascades of boosted classifiers for rapid object detection," in Proc. Pattern Recog., 2003, vol.2781, pp. 297-304.
44. Y. Freund and R. E. Schapire, "A short introduction to boosting," J. Jpn. Soc. Artif. Intell., vol.14, no.5, pp. 771-780, Sep. 1999.
45. R. E. Schapire, "The boosting approach to machine learning: An overview," in Proc. MSRI Workshop Nonlinear Estimation Classification, Berkeley, CA, Mar. 2002.
46. R. Meir and G. Rätsch, An Introduction to Boosting and Leveraging, vol.2600, Lecture Notes in Computer Science. Berlin, Germany: Springer-Verlag, 2003, ch. 4, pp. 118-183.
47. L. Breiman, J. Friedman, R. A. Olshen, and C. J. Stone, Classification and Regression Trees. London, U.K.: Chapman & Hall, 1984.
48. K. Tieu and P. Viola, "Boosting image retrieval," in Proc. Conf. Comput. Vis. Pattern Recog., Hilton Head Island, SC, 2000, pp. 228-235.
49. K. Tieu and P. Viola, "Boosting image retrieval," Int. J. Comput. Vis., vol. 56, no. 1/2, pp. 17-36, Jan. 2004.
50. M. S. Bartlett, G. Littlewort, I. Fasel, and J. R. Movellan, "Real time face detection and facial expression recognition: Development and applications to human computer interaction," in Proc. CVPR Workshop CVPR HCI, Madison, WI, Jun. 2003, p. 53.
51. C. Papageorgiou, M. Oren, and T. Poggio, "A general framework for object detection," in Proc. 6th Int. Conf. Comput. Vis., Bombay, India, 1998, pp. 555-562.
52. P. Viola and M. J. Jones, "Robust real-time face detection," Int. J. Comput. Vis., vol.57, no.2, pp. 137-154, May 2004.
53. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comput. Vis., vol.60, no.2, pp. 91-110, Nov. 2004.
54. H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool, "Speeded up robust features (SURF)," Comput. Vis. Image Underst., vol.110, no.3, pp. 346-359, Jun. 2008.
55. S. Hinz, D. Lenhart, and J. Leitloff, "Detection and tracking of vehicles in low frame rate aerial image sequences," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 36, no. 1/W51, 2007. [CD-ROM].
56. D. Lenhart, S. Hinz, J. Leitloff, and U. Stilla, "Automatic traffic monitoring based on aerial image sequences," Pattern Recognit. Image Anal., vol.18, no.3, pp. 400-405, Sep. 2008.
57. J. Leitloff, S. Hinz, and U. Stilla, "Detection of vehicle queues in QuickBird imagery of city areas," Photogrammetrie-Fernerkundung- Geoinformation, vol.4, pp. 315-325, 2006.
58. J. Leitloff, S. Hinz, and U. Stilla, "Automatic vehicle detection in satellite images," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol.36, no.3, pp. 221-227, 2006. [Online]. Available: http://www.ipk. bv.tum.de/pub/2006/leitloff-pcv06.pdf
59. S. Hinz, "Integrating local and global features for vehicle detection in high resolution aerial imagery," Int. Arch. Photogramm. Remote Sens. Spatial Inform. Sci., vol. 34, no. 3/W8, pp. 119-124, 2003.
60. C. Steger, "An unbiased detector of curvilinear structures," IEEE Trans. Pattern Anal. Mach. Intell., vol.20, no.2, pp. 113-125, Feb. 1998.
61. U. Ramer, "An iterative procedure for polygonal approximation of plane curves," Comput. Graph. Image Process., vol.1, pp. 244-256, 1972.
62. P. Huber, Robust Statistics. New York: Wiley, 1981.
63. C. V. Stewart, "Robust parameter estimation in computer vision," SIAM Rev., vol.41, no.3, pp. 513-537, Sep. 1999.
64. A. E. Beaton and J.W. Tukey, "The fitting of power series, meaning polynomials, illustrated on band-spectroscopic data," Technometrics, vol.16, no.2, pp. 147-185, May 1974.
65. C. Steger, M. Ulrich, and C. Wiedemann, Machine Vision Algorithms and Applications. Weilheim, Germany: Wiley-VCH Verlag GmbH & Co. KGaA, 2008.
66. P. W. Holland and R. E. Welsch, "Robust regression using iteratively reweighted least-squares," Commun. Statist. Theory Methods, vol.A6, no.9, pp. 813-827, 1977.
67. D. W. Marquardt, "An algorithm for least-squares estimation of nonlinear parameters," J. Soc. Ind. Appl. Math., vol.11, no.2, pp. 431-441, Jun. 1963. [Online]. Available: http://www.jstor.org/pss/2098941
68. C. Steger, Similarity Measures for Occlusion, Clutter, and Illumination Invariant Object Recognition, vol.2191, Lecture Notes on Computer Science. Berlin, Germany: Springer-Verlag, 2001, ch. 20, pp. 148-154.