Affine analysis of image sequences:
Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the e...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
1995
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| Schriftenreihe: | Distinguished dissertations in computer science
|
| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 URL des Erstveröffentlichers |
| Zusammenfassung: | Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then computed via 'affine epipolar geometry', and 'affine structure' is used to generate alternative views of the object and fill in partial views. The use of all available features (over multiple frames) and the incorporation of statistical noise properties substantially improves existing algorithms, giving greater reliability and reduced noise sensitivity |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xi, 210 pages) |
| ISBN: | 9780511526657 |
| DOI: | 10.1017/CBO9780511526657 |
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| 520 | |a Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then computed via 'affine epipolar geometry', and 'affine structure' is used to generate alternative views of the object and fill in partial views. The use of all available features (over multiple frames) and the incorporation of statistical noise properties substantially improves existing algorithms, giving greater reliability and reduced noise sensitivity | ||
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Datensatz im Suchindex
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| author | Shapiro, Larry S. |
| author_facet | Shapiro, Larry S. |
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| dewey-full | 006.4/2 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.4/2 |
| dewey-search | 006.4/2 |
| dewey-sort | 16.4 12 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| doi_str_mv | 10.1017/CBO9780511526657 |
| format | Electronic eBook |
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| id | DE-604.BV043942110 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:17Z |
| institution | BVB |
| isbn | 9780511526657 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029351080 |
| oclc_num | 967680188 |
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| physical | 1 online resource (xi, 210 pages) |
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| publishDate | 1995 |
| publishDateSearch | 1995 |
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| publisher | Cambridge University Press |
| record_format | marc |
| series2 | Distinguished dissertations in computer science |
| spelling | Shapiro, Larry S. Verfasser aut Affine analysis of image sequences Larry S. Shapiro Cambridge Cambridge University Press 1995 1 online resource (xi, 210 pages) txt rdacontent c rdamedia cr rdacarrier Distinguished dissertations in computer science Title from publisher's bibliographic system (viewed on 05 Oct 2015) Computer vision is a rapidly growing field which aims to make computers 'see' as effectively as humans. In this book Dr Shapiro presents a new computer vision framework for interpreting time-varying imagery. This is an important task, since movement reveals valuable information about the environment. The fully-automated system operates on long, monocular image sequences containing multiple, independently-moving objects, and demonstrates the practical feasibility of recovering scene structure and motion in a bottom-up fashion. Real and synthetic examples are given throughout, with particular emphasis on image coding applications. Novel theory is derived in the context of the affine camera, a generalisation of the familiar scaled orthographic model. Analysis proceeds by tracking 'corner features' through successive frames and grouping the resulting trajectories into rigid objects using new clustering and outlier rejection techniques. The three-dimensional motion parameters are then computed via 'affine epipolar geometry', and 'affine structure' is used to generate alternative views of the object and fill in partial views. The use of all available features (over multiple frames) and the incorporation of statistical noise properties substantially improves existing algorithms, giving greater reliability and reduced noise sensitivity Datenverarbeitung Mathematisches Modell Image processing / Mathematical models / Data processing Geometry, Affine / Data processing 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Erscheint auch als Druckausgabe 978-0-521-01978-1 Erscheint auch als Druckausgabe 978-0-521-55063-5 https://doi.org/10.1017/CBO9780511526657 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Shapiro, Larry S. Affine analysis of image sequences Datenverarbeitung Mathematisches Modell Image processing / Mathematical models / Data processing Geometry, Affine / Data processing |
| subject_GND | (DE-588)4113937-9 |
| title | Affine analysis of image sequences |
| title_auth | Affine analysis of image sequences |
| title_exact_search | Affine analysis of image sequences |
| title_full | Affine analysis of image sequences Larry S. Shapiro |
| title_fullStr | Affine analysis of image sequences Larry S. Shapiro |
| title_full_unstemmed | Affine analysis of image sequences Larry S. Shapiro |
| title_short | Affine analysis of image sequences |
| title_sort | affine analysis of image sequences |
| topic | Datenverarbeitung Mathematisches Modell Image processing / Mathematical models / Data processing Geometry, Affine / Data processing |
| topic_facet | Datenverarbeitung Mathematisches Modell Image processing / Mathematical models / Data processing Geometry, Affine / Data processing Hochschulschrift |
| url | https://doi.org/10.1017/CBO9780511526657 |
| work_keys_str_mv | AT shapirolarrys affineanalysisofimagesequences |