메뉴 건너뛰기




Volumn 49, Issue 1, 2002, Pages 79-89

Algorithmic fusion for more robust feature tracking

Author keywords

Algorithmic fusion; Combining multiple trackers; Feature tracking; Motion analysis

Indexed keywords

ALGORITHMS; ERROR DETECTION; FEATURE EXTRACTION; IMAGE ANALYSIS; KALMAN FILTERING; MATHEMATICAL MODELS; MEASUREMENT ERRORS; MOTION ESTIMATION; NORMAL DISTRIBUTION; SENSOR DATA FUSION;

EID: 0036698190     PISSN: 09205691     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1019833915960     Document Type: Article
Times cited : (25)

References (17)
  • 1
    • 0027543099 scopus 로고
    • A review of statistical data association techniques for motion correspondence
    • Cox, I.J. 1993. A review of statistical data association techniques for motion correspondence. International Journal of Computer Vision, 10(1):53-66.
    • (1993) International Journal of Computer Vision , vol.10 , Issue.1 , pp. 53-66
    • Cox, I.J.1
  • 2
    • 0030081415 scopus 로고    scopus 로고
    • An efficient implementation of Reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking
    • Cox, I.J. and Hingorani, S.L. 1996. An efficient implementation of Reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(2):138-150.
    • (1996) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.18 , Issue.2 , pp. 138-150
    • Cox, I.J.1    Hingorani, S.L.2
  • 3
    • 0032686948 scopus 로고    scopus 로고
    • Multi-classification: Reject criteria for the Bayesian combiner
    • Foggia, P., Sansone, C., Tortorella, F., and Vento, M. 1999. Multi-classification: Reject criteria for the Bayesian combiner. Pattern Recognition, 32:1435-1447.
    • (1999) Pattern Recognition , vol.32 , pp. 1435-1447
    • Foggia, P.1    Sansone, C.2    Tortorella, F.3    Vento, M.4
  • 12
    • 0029386827 scopus 로고
    • Estimation of optical flow based on higher order spatiotemporal derivative in interlaced and non-interlaced image sequences
    • Otte, M. and Nagel, H.-H. 1995. Estimation of optical flow based on higher order spatiotemporal derivative in interlaced and non-interlaced image sequences. Artificial Intelligence, 78:5-43.
    • (1995) Artificial Intelligence , vol.78 , pp. 5-43
    • Otte, M.1    Nagel, H.-H.2
  • 16
    • 0003743633 scopus 로고
    • Detection and tracking of point features
    • Carnegie Mellon University, Technical Report CMU-CS-91-132
    • Tomasi, C. and Kanade, T. 1991. Detection and tracking of point features. Carnegie Mellon University, Technical Report CMU-CS-91-132.
    • (1991)
    • Tomasi, C.1    Kanade, T.2
  • 17
    • 0026860706 scopus 로고
    • Methods of combining multiple classifiers and their applications to handwriting recognition
    • Xu, L., Kryzyzak, A., and Suen, C.Y. 1992. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Transactions on Systems, Man and Cybernetics, 22(3):418-435.
    • (1992) IEEE Transactions on Systems, Man and Cybernetics , vol.22 , Issue.3 , pp. 418-435
    • Xu, L.1    Kryzyzak, A.2    Suen, C.Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.