Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Cluster Computing
Published in: Cluster Computing 3/2019

03-03-2018

Forward looking infrared target matching algorithm based on depth learning and matrix double transformation

Authors: Rui Zeng, Ying-yan Wang

Published in: Cluster Computing | Special Issue 3/2019

Log in

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

search-config
loading …

Abstract

To effectively reduce traffic accidents caused by night driving and provide initiative whole system for car driving in environment of lower visibility, sub-model of pedestrians at night based on far infrared sensor technology was designed according to basic requirements of driver assistant system of cars in the industry. Original data source was extracted for this model via far infrared sensor and its ROIs were obtained by using grey statistical technology. Matching detection was conducted on data source on basis of constructing multi-scale probability template, and detection rate as well as rate of leak detection of designed models could be effectively improved via comprehensive treatment technology of multi-frame verification. Experiments show that probability template of this model is improved on matching precision compared with common methods in the industry. It is applicable to two kinds of traffic road conditions of suburb and downtown at the same time, so it has good practicability.
previous article Tiger hash based AdaBoost machine learning classifier for secured multicasting in mobile healthcare system
next article High performance Viterbi decoder design

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
Literature
1.
Su, J., Xu, Q.S., Liu, G.: A forward looking infrared target recognition algorithm based on edge matching. Acta Armamentarii 33(3), 271–277 (2012)
2.
Li, X., Cao, Z., Yan, R., et al.: Forward-looking infrared 3D target tracking via combination of particle filter and SIFT. Proc. SPIE Int. Soc. Opt. Eng. 8918(48), 08 (2013)
3.
Zheng, C.Y., Li, H.: Small infrared target detection based on harmonic and sparse matrix decomposition. Opt. Eng. 52(6), 066401 (2013)CrossRef
4.
Yilmaz, A., Shafique, K., Shah, M.: Target tracking in airborne forward looking infrared imagery. Image Vis. Comput. 21(7), 623–635 (2003)CrossRef
5.
Rizvi, S.A., Nasrabadi, N.M.: Neural network algorithms for automatic target recognition using forward-looking infrared imagery: a survey. Proc. Indian Acad. Sci. A 67(2), 243–276 (2001)
6.
Borghys, D.C.J., Acheroy, M.P.J.: Long-range automatic detection of small targets in sequences of noisy thermal infrared images. Proc. SPIE Int. Soc. Opt. Eng. 2235, 4–8 (1994)
7.
Gianluca, P., Stefano, E.: Relevance-based template matching for tracking targets in FLIR imagery. Sensors 14(8), 14106–14130 (2014)CrossRef
8.
Bouteiller, A., Herault, T., Bosilca, G., et al.: Algorithm-based fault tolerance for dense matrix factorizations, multiple failures and accuracy. ACM Trans. Parallel Comput. 1(2), 1–28 (2015)CrossRef
9.
Jiang, H., Liao, G., Qu, Y.: Compensation of clutter spectrum for airborne forward-looking radar based on the clutter subspace transformation. In: Proceedings of the International Radar Conference Surveillance for a Safer World. IEEE, pp. 1–4 (2009)
10.
Litvak, S., Brailovsky, L., Yanir, T.: Learning based estimation of hand and finger pose: US, US 20130236089 A1 [P] (2016)
11.
Young, S.S., Kwon, H., Nasrabadi, N.M.: Adaptive target detection in FLIR imagery using the eigen space separation transform and principal component analysis. Proc. SPIE Int. Soc. Opt. Eng. 85(11), 26 (2003)
12.
Raghubar, K.P., Barnes, M.A., Hecht, S.A.: Working memory and mathematics: a review of developmental, individual difference, and cognitive approaches. Learn. Individ. Differ. 20(2), 110–122 (2010)CrossRef
13.
Yeung, F., Levinson, S.F., Fu, D., et al.: Feature-adaptive motion tracking of ultrasound image sequences using a deformable mesh. IEEE Trans. Med. Imaging 17(6), 945–956 (1998)CrossRef
14.
Feldman, V., Gopalan, P., Khot, S., et al.: New results for learning noisy parities and halfspaces. In: Proceedings of the IEEE Symposium on Foundations of Computer Science, 2006. FOCS ‘06. IEEE, pp. 563–574 (2006)
15.
Zhang, Z., Ou, J., Li, D., Zhang, S.: Optimization design of coupling beam metal damper in shear wall structures. Appl. Sci. 7(2), 137 (2017)CrossRef
16.
Pan, W., Chen, S., Feng, Z.: Automatic clustering of social tag using community detection. Appl. Math. Inf. Sci. 7(2), 675–681 (2013)CrossRef
17.
Liu, C., Li, Y., Zhang, Y., Yang, C., Hongbin, W., Qin, J., Cao, Y.: Solution-processed, undoped, deep-blue organic light-emitting diodes based on starburst oligofluorenes with a planar triphenylamine core. Chem. Eur. J. 18(22), 6928–6934 (2012)CrossRef
Metadata
Title
Forward looking infrared target matching algorithm based on depth learning and matrix double transformation
Authors
Rui Zeng
Ying-yan Wang
Publication date
03-03-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 3/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2245-5

Other articles of this Special Issue 3/2019

Cluster Computing 3/2019 Go to the issue

OriginalPaper

Evolution model and simulation of logistics outsourcing for manufacturing enterprises based on multi-agent modeling

OriginalPaper

Mobile sink discovery mechanism in wireless sensor networks with duty cycles

OriginalPaper

Region segmentation model for wireless sensor networks considering optimal energy conservation constraints

OriginalPaper

Feature selection for software effort estimation with localized neighborhood mutual information

OriginalPaper

Study on relationship between green logistics activity and logistics performance

OriginalPaper

The application of agglomerative hierarchical spatial clustering algorithm in tea blending

Premium Partner

    Image Credits