Top

Published in:

2016 | OriginalPaper | Chapter

An Evaluation of SETh—The Method for Long-Term Feature Tracking

Authors : Karol Jędrasiak, Aleksander Nawrat

Published in: Innovative Simulation Systems

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The chapter presents a novel long-term object tracking method called SETh. It is an adaptive tracking by detection method which allows near real-time tracking within challenging sequences. The algorithm consists of three stages: detection, verification and learning. In order to measure the performance of the method a video data set consisting of more than a hundred videos was created and manually labelled by a human. Quality of the tracking by SETh was compared against five state-of-the-art methods. The presented method achieved results comparable and mostly exceeding the existing methods, which proves its capability for real life applications like e.g. vision-based control of UAVs.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter GPU-Based Parameters Estimation for Anisotropic Diffusion

next chapter The System for Augmented Reality Motion Measurements Visualization

Jędrasiak, K., Daniec, K., Nawrat, A., Koteras, R.: Wykorzystanie kamer termowizyjnych w systemach dozoru wizyjnego infrastruktury krytycznej sieci dystrybucyjnych gazu. Przegląd Elektrotechniczny 88, 90–97 (2012)

Ryt, A., Sobel, D., Kwiatkowski, J., Domzal, M., Jedrasiak, K., Nawrat, A.: Real-time Laser Point Tracking, Computer Vision and Graphics. Lecture Notes in Computer Science, vol. 8671. pp. 542–551 (2014)

Kuś, Z., Nawrat, A.: Object tracking in a picture during rapid camera movements. In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 77–91, ISBN 978-3-319-00368-9 (2013)

Pritch, A.Y., Ratovitch, S., Hendel, A., Peleg, S.: Clustered synopsis of surveillance video. In: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009. AVSS’09, IEEE (2009)

Pritch, Y., Rav-Acha, A., Peleg, S.: Video Synopsis. The Hebrew University of Jerusalem (2014)

Bibik, P., Zasuwa, M., Zugaj, M.: Research and training simulator of unmanned quadrotor. In: 18th IEEE International Conference on Methods and Models in Automation and Robotics (MMAR), pp. 403–407 (2013)

Babiarz, A., Jaskot, K., Koralewicz, P.: The control system for autonomous mobile platform. In: Advanced Technologies for Intelligent Systems of National Border Security. Studies in Computational Intelligence, vol. 440, pp. 15–28 (2013)

Bereska, D., Balcewicz, R., Garczyński, M.: Implementacja magistrali CAN i protokołu CANopen w robocie edukacyjnym. Szybkobieżne Pojazdy Gąsienicowe 1, 157–162 (2008)

Gałuszka, A., Skrzypczyk, K., Bereska, D., Pacholczyk, M.: Re-handling operations in small container terminal operated by reach stackers. World Acad. Sci. Eng. Technol. 70, 674–677 (2010)

10.

Babiarz, A., Bieda, R., Jaskot, K.: A distributed control group of mobile robots in a limited area with a vision system. Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 157–175. ISBN 978-3-319-00368-9 (2013)

11.

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

12.

Kwon, J., Lee, K.M.: Visual tracking decomposition. In: Computer Vision and Pattern Recognition (CVPR) (2010)

13.

Wu, A.: Towards linear-time incremental structure from motion. In: IEEE International Conference on 3D Vision, pp. 127–134 (2013)

14.

Tomasi, C., Kanade, T.: Detection and tracking of point features. Carnegie Mellon University Technical Report CMU-CS-91-132 (1991)

15.

Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34, 1409–1422 (2012)CrossRef

16.

Kalal, Z., Mikolajczyk, K., Matas, J.: Forward-backward error: automatic detection of tracking failures. In: International Conference on Pattern Recognition, pp. 23–26 (2010)

17.

Adam, A., Rivlin, E., Shimshoni, I.: Robust fragments-based tracking using the integral histogram. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1 (2006)

18.

Babenko, Boris, Yang, Ming-Hsuan, Belongie, Serge: Robust object tracking with online multiple instance learning. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1619–1632 (2011)CrossRef

19.

Breitenstein, M.D., Reichlin, F., Leibe, B., Koller-Meier, E., Gool, L.V.: Robust tracking-by-detection using a detector confidence particle filter. In: Proceedings of IEEE 12th International Conference Computer Vision (2009)

20.

Grabner, H., Bischof, H.: On-line boosting and vision. In: CVPR (2006)

21.

Grabner, H., Leistner, C., Bischof, H.: Semi-supervised on-line boosting for robust tracking. In: Proceedings of 10th European Conference on Computer Vision (2008)

22.

Jedrasiak, K., Andrzejczak, M., Nawrat, A.: SETh: the method for long-term object tracking. In: Computer Vision and Graphics. Lecture Notes in Computer Science, vol. 8671, pp. 302–315 (2014)

23.

Jedrasiak, K., Nawrat, A.: Fast color recognition algorithm for robotics. Probl. Eksploatacji. Maintenance Problems (Quarterly), pp. 69–76 (2008)

24.

Nawrat, A., Jedrasiak, K.: SETh system spatio-temporal object tracking using combined color and motion feature. Advanced robotics, control and advanced manufacturing systems. In: Proceedings of the 9th WSEAS International Conference on Robotics, Control and Manufacturing Technology (ROCOM’09), pp. 67–72 (2009)

25.

Jędrasiak, K., Nawrat, A.: Image recognition technique for unmanned aerial vehicles. In: Computer Vision and Graphics. Lecture Notes in Computer Science, vol. 5337, pp. 391–399 (2009)

26.

Leutenegger, S., Chli, M., Siegwart, R.: Brisk: binary robust invariant scalable keypoints. In: ICCV’11, pp. 2548–2555 (2010)

27.

Alahi, A., Ortiz, R., Vandergheynst, P.: FREAK: fast retina keypoint. In: IEEE Conference on Computer Vision and Pattern Recognition (2012)

28.

Ester, M., Kriegel, H.-P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD’96), pp. 226–231 (1996)

29.

FLIR, dostępne na: http://www.flir.com/PL (Data pobrania zasobu: 05-03-2014)

30.

Toussaint, G.T.: Solving geometric problems with the rotating calipers. Proc. IEEE Melecon 83, A10 (1983)

31.

Oron, S., Bar-Hillel, A., Levi, D., Avidan, S.: Locally orderless tracking. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2012)

32.

Morzy, T.: Eksploracja Danych – Metody i Algorytmy. Wydawnictwo Naukowe PWN, Warszawa (2013)

33.

https://www.dropbox.com/sh/v705ac32e8006z7/s1ezUqplcE

34.

Demski, P., Grzejszczak, T., Jędrasiak, K., Mikulski, M.: Automatic targeting sentry turret for distributed systems. In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 47–55, ISBN 978-3-319-00368-9 (2013)

35.

Sroka, M., Ściegienka, P., Babiarz, A., Jaskot, K.: Prototyp bezzałogowego pojazdu podwodnego – układ stabilizacji i utrzymania zadanego kursu. Przegląd Elektrotechniczny 89, 205–217 (2013)

36.

Jaskot, K., Babiarz, A., Sroka, M., Ściegienka, P.: Prototyp bezzałogowego pojazdu podwodnego – konstrukcja mechaniczna, panel operatora. Przegląd Elektrotechniczny 89, 52–67 (2013)

37.

Iwaneczko, P., Jedrasiak, K., Daniec, K., Nawrat, A.: A prototype of unmanned aerial vehicle for image acquisition. In: Computer Vision and Graphics. Lecture Notes in Computer Science, vol. 7594, pp. 87–94. Springer, Berlin (2013)

38.

Czapla, T., Wrona, J.: Technology development of military applications of unmanned ground vehicles. In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 293–309. ISBN 978-3-319-00368-9 (2013)

39.

Niezgoda, T., Panowicz, R., Sybilski, K., Barnat, W.: Numerical analysis of missile impact being shot by rocket propelled grenades with rod armour. WIT Trans. Model. Simul. 51, 625–633 (2011)CrossRef

40.

Kuś, Z., Nawrat, A.M.: The limitation for the angular velocity of the camera head during object tracking with the use of the UAV. In: Innovative Control Systems for Tracked Vehicle Platforms. Studies in Systems, Decisions and Control, vol. 2, pp. 127–145 (2014)

41.

Jedrasiak, K., Nawrat, A., Daniec, K., Koteras, R., Mikulski, M., Grzejszczak, T.: A prototype device for concealed weapon detection using IR and CMOS cameras fast image fusion. In: Computer Vision and Graphics. Lecture Notes in Computer Science, vol. 7594, pp. 423–432, Springer, Berlin (2013)

42.

Bereska, D., Daniec, K., Fraś, S., Jędrasiak, K., Malinowski, M., Nawrat, A.: System for multi-axial mechanical stabilization of digital camera. In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 117–189. ISBN 978-3-319-00368-9 (2013)

43.

Bereska, D., Daniec, K., Jędrasiak, K., Nawrat, A.: Gyro-stabilized platform for multispectral image acquisition. In: Vision Based Systems for UAV Applications. Studies in Computational Intelligence, vol. 481, pp. 115–121. ISBN 978-3-319-00368-9 (2013)

Title: An Evaluation of SETh—The Method for Long-Term Feature Tracking
Authors: Karol Jędrasiak
Aleksander Nawrat
Publisher: Springer International Publishing
Book: Innovative Simulation Systems
Print ISBN: 978-3-319-21117-6

Electronic ISBN: 978-3-319-21118-3

Copyright Year: 2016
DOI: https://doi.org/10.1007/978-3-319-21118-3_9

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner