Jet-Based Local Image Descriptors

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Standard

Jet-Based Local Image Descriptors. / Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg; Pedersen, Kim Steenstrup.

Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer, 2012. p. 638-650 (Lecture Notes in Computer Science, Vol. 7584).

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Harvard

Larsen, ABL, Darkner, S, Dahl, AL & Pedersen, KS 2012, 'Jet-Based Local Image Descriptors'. in Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer, pp. 638-650. Lecture Notes in Computer Science, vol. 7584, , 10.1007/978-3-642-33712-3_46

APA

Larsen, A. B. L., Darkner, S., Dahl, A. L., & Pedersen, K. S. (2012). Jet-Based Local Image Descriptors. In Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. (pp. 638-650). Springer. (Lecture Notes in Computer Science, Vol. 7584). 10.1007/978-3-642-33712-3_46

CBE

Larsen ABL, Darkner S, Dahl AL, Pedersen KS. 2012. Jet-Based Local Image Descriptors. In Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer. pp. 638-650. (Lecture Notes in Computer Science, Vol. 7584). Available from: 10.1007/978-3-642-33712-3_46

MLA

Larsen, Anders Boesen Lindbo et al. "Jet-Based Local Image Descriptors". Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer. 2012. 638-650. (Lecture Notes in Computer Science, Volume 7584). Available: 10.1007/978-3-642-33712-3_46

Vancouver

Larsen ABL, Darkner S, Dahl AL, Pedersen KS. Jet-Based Local Image Descriptors. In Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer. 2012. p. 638-650. (Lecture Notes in Computer Science, Vol. 7584). Available from: 10.1007/978-3-642-33712-3_46

Author

Larsen, Anders Boesen Lindbo; Darkner, Sune; Dahl, Anders Lindbjerg; Pedersen, Kim Steenstrup / Jet-Based Local Image Descriptors.

Computer Vision – ECCV 2012: Workshops and Demonstrations, Part III. Springer, 2012. p. 638-650 (Lecture Notes in Computer Science, Vol. 7584).

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2012

Bibtex

@inbook{388ea09d8af44d00ab25952cbd0ec3a1,
title = "Jet-Based Local Image Descriptors",
publisher = "Springer",
author = "Larsen, {Anders Boesen Lindbo} and Sune Darkner and Dahl, {Anders Lindbjerg} and Pedersen, {Kim Steenstrup}",
year = "2012",
doi = "10.1007/978-3-642-33712-3_46",
isbn = "978-3-642-33711-6",
series = "Lecture Notes in Computer Science",
pages = "638-650",
booktitle = "Computer Vision – ECCV 2012",

}

RIS

TY - GEN

T1 - Jet-Based Local Image Descriptors

A1 - Larsen,Anders Boesen Lindbo

A1 - Darkner,Sune

A1 - Dahl,Anders Lindbjerg

A1 - Pedersen,Kim Steenstrup

AU - Larsen,Anders Boesen Lindbo

AU - Darkner,Sune

AU - Dahl,Anders Lindbjerg

AU - Pedersen,Kim Steenstrup

PB - Springer

PY - 2012

Y1 - 2012

N2 - We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on the recently released DTU Robot dataset. We demonstrate how the use of higher-order image structures enables us to reduce the descriptor dimensionality while still achieving very good performance. The descriptors are tested in a variety of scenarios including large changes in scale, viewing angle and lighting. We show that the proposed jet-based descriptor is superior to state-of-the-art for DoG interest points and show competitive performance for the other tested interest points.

AB - We present a general novel image descriptor based on higherorder differential geometry and investigate the effect of common descriptor choices. Our investigation is twofold in that we develop a jet-based descriptor and perform a comparative evaluation with current state-of-the-art descriptors on the recently released DTU Robot dataset. We demonstrate how the use of higher-order image structures enables us to reduce the descriptor dimensionality while still achieving very good performance. The descriptors are tested in a variety of scenarios including large changes in scale, viewing angle and lighting. We show that the proposed jet-based descriptor is superior to state-of-the-art for DoG interest points and show competitive performance for the other tested interest points.

U2 - 10.1007/978-3-642-33712-3_46

DO - 10.1007/978-3-642-33712-3_46

SN - 978-3-642-33711-6

BT - Computer Vision – ECCV 2012

T2 - Computer Vision – ECCV 2012

T3 - Lecture Notes in Computer Science

T3 - en_GB

SP - 638

EP - 650

ER -