Analytic Solutions for Multiple Motions

C. Mota; I. Stuke; E. Barth

doi:10.1109/ICIP.2001.958644

Analytic Solutions for Multiple Motions

C. Mota, I. Stuke, E. Barth

Abstract

A novel framework for single and multiple motion estimation is presented. It is based on a generalized structure tensor that contains blurred products of directional derivatives. The order of differentiation increases with the number of motions but more general linear filters can be used instead of derivatives. From the general framework, a hierarchical algorithm for motion estimation is derived and its performance is demonstrated on a synthetic sequence.

Originalsprache	Englisch
Seiten	917-920
Seitenumfang	4
DOIs	https://doi.org/10.1109/ICIP.2001.958644
Publikationsstatus	Veröffentlicht - 01.01.2001
Veranstaltung	IEEE International Conference on Image Processing 2001 - Thessaloniki, Griechenland Dauer: 07.10.2001 → 10.10.2001 Konferenznummer: 58802

Tagung, Konferenz, Kongress

Tagung, Konferenz, Kongress	IEEE International Conference on Image Processing 2001
Kurztitel	ICIP 2001
Land/Gebiet	Griechenland
Ort	Thessaloniki
Zeitraum	07.10.01 → 10.10.01

UN SDGs

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SDG 3 – Gesundheit und Wohlergehen
SDG 9 – Industrie, Innovation und Infrastruktur

Dokumente

10.1109/ICIP.2001.958644

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https://www.scopus.com/pages/publications/0035158891

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AU - Stuke, I.

AU - Barth, E.

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N2 - A novel framework for single and multiple motion estimation is presented. It is based on a generalized structure tensor that contains blurred products of directional derivatives. The order of differentiation increases with the number of motions but more general linear filters can be used instead of derivatives. From the general framework, a hierarchical algorithm for motion estimation is derived and its performance is demonstrated on a synthetic sequence.

AB - A novel framework for single and multiple motion estimation is presented. It is based on a generalized structure tensor that contains blurred products of directional derivatives. The order of differentiation increases with the number of motions but more general linear filters can be used instead of derivatives. From the general framework, a hierarchical algorithm for motion estimation is derived and its performance is demonstrated on a synthetic sequence.

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U2 - 10.1109/ICIP.2001.958644

DO - 10.1109/ICIP.2001.958644

M3 - Conference Papers

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EP - 920

T2 - IEEE International Conference on Image Processing 2001

Y2 - 7 October 2001 through 10 October 2001

ER -

Analytic Solutions for Multiple Motions

Abstract

Tagung, Konferenz, Kongress

UN SDGs

Dokumente

Weitere Links

Fingerprint

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