Skip to main content
SpringerLink
Log in

Optimal feature points for tracking multiple moving objects in active camera model

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Object tracking is an important task in computer vision that is essential for higher level vision applications such as surveillance systems, human-computer interaction, industrial control, smart compression of video, and robotics. Tracking, however, cannot be easily accomplished due to challenges such as real-time processing, occlusions, changes in intensity, abrupt motions, variety of objects, and mobile platforms. In this paper, we propose a new method to estimate and eliminate the camera motion in mobile platforms, and accordingly, we propose a set of optimal feature points for accurate tracking. Experimental results on different videos show that the proposed method estimates camera motion very well and eliminate its effect on tracking moving objects. And the use of optimal feature points results in a promising tracking. The proposed method in terms of accuracy and processing time has desirable results compared to the state-of-the-art methods.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Aggarwal JK, Cai Q (1997) Human motion analysis: A review. In: In Nonrigid and Articulated Motion Workshop, pp 90–102

  2. Argyros AA, Lourakis MI (2004) Real-time tracking of multiple skin-colored objects with a possibly moving camera. In: European Conference on Computer Vision, pp 368–379

  3. Beyan C, Temizel A (2012) Adaptive mean-shift for automated multi-object tracking. IET Comput Vis 6(1):1–12

    Article  MathSciNet  Google Scholar 

  4. Chen CH, Cheng C, Page D, Koschan A, Abidi M (2006) A moving object tracked by a mobile robot with real-time obstacles avoidance capacity. In: International Conference on Pattern Recognition, pp 1091–1094

  5. Chen Y, Zhang Rh, Shang L (2014) A novel method of object detection from a moving camera based on image matching and frame coupling. PLoS ONE 9(10):e109809. doi:10.1371/journal.pone.0109809

    Article  Google Scholar 

  6. Choi W, Savarese S (2010) Multiple target tracking in world coordinate with single, minimally calibrated camera. In: European Conference on Computer Vision, pp 553–567

  7. Collins RT, Zhou X, Teh SK (2005) An open source tracking testbed and evaluation web site. In: IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, pp 17–24

  8. Dhillon PS, Orozco J, Gonzalez J (2008) Real-time monocular face tracking using an active camera. Electronic Letters on Computer Vision and Image Analysis:1–7

  9. Doyle DD, Jennings AL, Black JT (2014) Optical flow background estimation for real-time pan/tilt camera object tracking. Measurement 48:195–207

    Article  Google Scholar 

  10. Giesbrecht J, Goldsmith P, Pieper J (2010) Control strategies for visual tracking from a moving platform. In: Canadian Conference on Electrical and Computer Engineering, pp 1–7

  11. Haritaoglu I, Harwood D, Davis LS (2000) W4: Real-time surveillance of people and their activities. IEEE Trans Pattern Anal Mach Intell 22(8):809–830

    Article  Google Scholar 

  12. Hashemzadeh M, Pan G, Yao M (2014) Counting moving people in crowds using motion statistics of feature-points. Multimed Tools Appl 72:453–487

    Article  Google Scholar 

  13. He S, Yang Q, Lau RW, Wang J, HYang M (2013) Visual tracking via locality sensitive histograms. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 2427–2434

  14. Hsieh YS, Su YC, Chen LG (2012) Robust moving object tracking and trajectory prediction for visual navigation in dynamic environments. In: IEEE International Conference on Consumer Electronics, pp 696–697

  15. Huang C, Wu B, Nevatia R (2008) Robust object tracking by hierarchical association of detection responses. In: European Conference on Computer Vision, pp 788–801

  16. Jung B, Sukhatme GS (2004) Detecting moving objects using a single camera on a mobile robot in an outdoor environment. In: International Conference on Intelligent Autonomous Systems, pp 980–987

  17. Jung YK, Lee KW, Ho YS (2002) Feature-based object tracking with an active camera. Lect Notes Comput Sci 2532:1137–1144

    Article  Google Scholar 

  18. Kadim Z, Daud MM, Radzi SSM, Samudin N, Woon HH (2013) Method to detect and track Moving object in non-static PTZ camera. Int MultiConf Eng Comput Sci 1

  19. Kim IS, Choi HS, Yi KM, Choi JY, Kong SG (2010) Intelligent visual surveillance: A survey. Int J Control, Autom Syst 8(5):926–939

    Article  Google Scholar 

  20. Kim S, Lee S, Kim S, Lee J (2009) Object tracking of mobile robot using moving color and shape information for the aged walking. Int J Adv Sci Technol 3:59–68

    Google Scholar 

  21. Kundu A, Jawahar CV, Krishna KM (2010) Real-time moving object detection from a freely moving monocular camera. In: IEEE International Conference on Robotics and Biomimetics , pp 1635–1640

  22. Kuo CH, Huang C, Nevatia R (2010) Multi-target tracking by on-line learned discriminative appearance models

  23. Kuo CH, Nevatia R (2011) How does person identity recognition help multi-person tracking?. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 1217–1224

  24. Lefevre S, Vincent N (2004) Real time multiple object tracking based on active contours. In: Image Analysis and Recognition, pp 606–613

  25. Lee KW, Ryu SW, Lee SJ, Park KT (1998) Motion based object tracking with mobile camera. Electron Lett 34(3):256–258

    Article  Google Scholar 

  26. Li Y, Huang C, Nevatia R (2009) Learning to associate: Hybridboosted multi-target tracker for crowded scene. In: IEEE Conference on Computer Vision and Pattern Recognition , pp 2953–2960

  27. Lim JS, Kim WH (2005) Detection and tracking multiple pedestrians from a moving camera. Lect Notes Comput Sci 3804:527–534

    Article  Google Scholar 

  28. Lim JS, Kim WH (2013) Detecting and tracking of multiple pedestrians using motion, color information and the AdaBoost algorithm. Multimed Tools Appl 65 (1):161–179

    Article  MathSciNet  Google Scholar 

  29. Lucas BD, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: International Joint Conference on Artificial Intelligence, pp 674–679

  30. Manigandan M, Malathi G, Madhavi N (2010) Wireless vision based moving object tracking robot through perceptual color space. In: International Conference on Emerging Trends in Robotics and Communication Technologies, pp 20–25

  31. Mao H, Yang C, Abousleman GP, Si J (2010) Automated multiple target detection and tracking in UAV videos. In: Airborne Intelligence, Surveillance, Reconnaissance Systems and Applications, pp 76680J–76680J

  32. Mao H, Yang C, Si J, Abousleman GP (2010) Automated multiple target detection and tracking in UAV Videos. In: Proceedings of SPIE 7668, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications VII, pp 76680J–76680J

  33. Micheloni C, Foresti GL (2005) Zoom on target while tracking. In: IEEE International Conference on Image Processing, pp 111–117

  34. Murray D, Basu A (1994) Motion tracking with an active camera. IEEE Trans Pattern Anal Mach Intell 16(5)

  35. Ning J, Zhang L, Zhang D, Wu C (2012) Robust mean-shift tracking with corrected background-weighted histogram. IET Comput Vis 6(1):62–69

    Article  MathSciNet  Google Scholar 

  36. Piccardi M (2004) Background subtraction techniques: A review. In: International Conference on Systems, Man and Cybernetics, pp 3099–3104

  37. Poppe R (2007) Vision-based human motion analysis: An overview. Comput Vis Image Underst 108(1):4–18

    Article  Google Scholar 

  38. Rosenberg Y, Werman M (1998) Real-time object tracking from a moving video camera: A software approach on a PC. In: IEEE Workshop on Applications of Computer Vision , pp 238–238

  39. Selsis M, Vieren C, Cabestaing F (1995) Automatic tracking and 3D localization of moving objects by active contour models. In: Intelligent Vehicles’ 95 Symposium, pp 96–100

  40. Shi J, Tomasi C (1994) Good features to track. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 593–600

  41. Siam M, ElSayed R, ElHelw M (2012) On-board multiple target detection and tracking on camera-equipped aerial vehicles. In: IEEE International Conference on Robotics and Biomimetics, pp 2399–2405

  42. Stauffer C, Grimson WEL (2000) Learning patterns of activity using real-time tracking. IEEE Trans Pattern Anal Mach Intell 22(8):747–757

    Article  Google Scholar 

  43. Stolkin R, Rees D, Talha M, Florescu I (2012) Bayesian fusion of thermal and visible spectra camera data for region based tracking with rapid background adaptation. In: IEEE Conference on Multisensor Fusion and Integration for Intelligent Systems, pp 192–199

  44. Talukder A, Goldberg S, Matthies L, Ansar A (2003) Real-time detection of moving objects in a dynamic scene from moving robotic vehicles. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 1308–1313

  45. Tutorial: http://www.emgu.com/wiki/index.php/Tutorial

  46. Vezzani R, Cucchiara R (2010) Video Surveillance Online Repository (ViSOR): An integrated framework. Multimed Tools Appl 50:359–380

    Article  Google Scholar 

  47. VIVID Tracking Evaluation Web Site: http://vision.cse.psu.edu/data/vividEval/datasets/datasets.html

  48. Wu B, Nevatia R (2007) Detection and tracking of multiple, partially occluded humans by bayesian combination of edgelet based part detectors. Int J Comput Vis 75 (2):247–266

    Article  Google Scholar 

  49. Wu Y, Lim J, Yang M (2013) Online object tracking: A benchmark. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 2411–2418

  50. Xiang G (2009) Real-time follow-up tracking fast moving object with an active camera. In: International Congress on Image and Signal Processing, pp 1–4

  51. Xiang G, Lin Z (2009) Tracking object under intense disturbance based on adaptive histogram with an active camera. In: International Conference on Mechatronics and Automation, pp 1162–1166

  52. Yao F, Sekmen A, Malkani M (2008) A novel method for real-time multiple moving targets detection from moving IR camera. In: International Conference on Pattern Recognition, pp 1–4

  53. Yilmaz A, Javed O, Shah M (2006) Object tracking: A survey. ACM Comput Surv 38(4)

  54. Yilmaz A, Li X, Shah M (2004) Contour-based object tracking with occlusion handling in video acquired using mobile cameras. IEEE Trans Pattern Anal Mach Intell 26(11):1531–1536

    Article  Google Scholar 

  55. Youngwoo Y, Hosub Y, Jaehong K (2012) Person following with a RGB-D camera for mobile robots. In: International Conference on Ubiquitous Robots and Ambient Intelligence, p 191

  56. Zaki M, Youssef M (2009) TNRAC: A system for tracking multiple moving non-rigid objects using an active camera. Proc Signal, Image Video 3(2):145–155

    Article  Google Scholar 

  57. Zhang K, Zhang L, Yang MH (2012) Real-time Compressive Tracking. In: Proceedings of the European Conference on Computer Vision, pp 864–877

  58. Zhang R, Ding J (2012) Object tracking and detecting based on adaptive background subtraction. Proc Eng 29:1351–1355

    Article  Google Scholar 

  59. Zhao T, Nevatia R (2004) Tracking multiple humans in crowded environment. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 406–413

Download references

Author information

Authors and Affiliations

  1. Department of IT and Computer Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran

    Aziz Karamiani & Nacer Farajzadeh

Authors
  1. Aziz Karamiani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nacer Farajzadeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nacer Farajzadeh.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Karamiani, A., Farajzadeh, N. Optimal feature points for tracking multiple moving objects in active camera model. Multimed Tools Appl 75, 10999–11017 (2016). https://doi.org/10.1007/s11042-015-2823-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-015-2823-y

Keywords

Search

Navigation