### Abstract

Most image analysis/understanding applications require accurate computation of camera motion parameters. However, in multimedia applications, particularly in video parsing, the exact camera motion parameters such as the panning and/or zooming rates are not needed. The detection-i.e., a binary decision-of camera motion is all that is required to avoid declaring a false scene change. As camera motions can induce false scene changes for video parsing algorithms, we propose a fast algorithm to detect such camera motions: camera zoom and pan. As the algorithm is only expected produce a binary decision, without the exact panning/zooming rates, the proposed algorithm runs on a reduced data set, namely the projection data. The algorithm begins with a central portion of the image and computes the projection data (or the line integrals along the x- or y- axis) to turn the 2-D image data into a 1-D data. This projected 1-D data is further processed via correlation processing to detect camera zoom and pan. Working with projection data saves processing time by an order of magnitude, since for instance, a 2-D correlation takes N
^{2} multiplies per point, however a 1-D correlation takes N multiplies per point. The efficacy of the proposed algorithm is tested for a number of image sequences and the algorithm is shown to be successful in detecting camera motions. The proposed algorithm is expected to be beneficial for video parsers working with Motion-JPEG data stream where motion vectors are not available.

Original language | English |
---|---|

Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |

Editors | D. Sinha |

Pages | 78-87 |

Number of pages | 10 |

Volume | 3303 |

DOIs | |

Publication status | Published - 1998 |

Externally published | Yes |

Event | Real-Time Imaging III - San Jose, CA, United States Duration: 1998 Jan 26 → 1998 Jan 26 |

### Other

Other | Real-Time Imaging III |
---|---|

Country | United States |

City | San Jose, CA |

Period | 98/1/26 → 98/1/26 |

### Fingerprint

### Keywords

- Camera motion detection
- Scene change detection
- Video library
- Video parser

### ASJC Scopus subject areas

- Electrical and Electronic Engineering
- Condensed Matter Physics

### Cite this

*Proceedings of SPIE - The International Society for Optical Engineering*(Vol. 3303, pp. 78-87) https://doi.org/10.1117/12.302417

**A fast algorithm for detection of camera motion.** / Kim, Hyeokman; Kwon, Tae Hoon; Kim, Woon Kyung; Rhee, Byung D.; Song, S. M H.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of SPIE - The International Society for Optical Engineering.*vol. 3303, pp. 78-87, Real-Time Imaging III, San Jose, CA, United States, 98/1/26. https://doi.org/10.1117/12.302417

}

TY - GEN

T1 - A fast algorithm for detection of camera motion

AU - Kim, Hyeokman

AU - Kwon, Tae Hoon

AU - Kim, Woon Kyung

AU - Rhee, Byung D.

AU - Song, S. M H

PY - 1998

Y1 - 1998

N2 - Most image analysis/understanding applications require accurate computation of camera motion parameters. However, in multimedia applications, particularly in video parsing, the exact camera motion parameters such as the panning and/or zooming rates are not needed. The detection-i.e., a binary decision-of camera motion is all that is required to avoid declaring a false scene change. As camera motions can induce false scene changes for video parsing algorithms, we propose a fast algorithm to detect such camera motions: camera zoom and pan. As the algorithm is only expected produce a binary decision, without the exact panning/zooming rates, the proposed algorithm runs on a reduced data set, namely the projection data. The algorithm begins with a central portion of the image and computes the projection data (or the line integrals along the x- or y- axis) to turn the 2-D image data into a 1-D data. This projected 1-D data is further processed via correlation processing to detect camera zoom and pan. Working with projection data saves processing time by an order of magnitude, since for instance, a 2-D correlation takes N 2 multiplies per point, however a 1-D correlation takes N multiplies per point. The efficacy of the proposed algorithm is tested for a number of image sequences and the algorithm is shown to be successful in detecting camera motions. The proposed algorithm is expected to be beneficial for video parsers working with Motion-JPEG data stream where motion vectors are not available.

AB - Most image analysis/understanding applications require accurate computation of camera motion parameters. However, in multimedia applications, particularly in video parsing, the exact camera motion parameters such as the panning and/or zooming rates are not needed. The detection-i.e., a binary decision-of camera motion is all that is required to avoid declaring a false scene change. As camera motions can induce false scene changes for video parsing algorithms, we propose a fast algorithm to detect such camera motions: camera zoom and pan. As the algorithm is only expected produce a binary decision, without the exact panning/zooming rates, the proposed algorithm runs on a reduced data set, namely the projection data. The algorithm begins with a central portion of the image and computes the projection data (or the line integrals along the x- or y- axis) to turn the 2-D image data into a 1-D data. This projected 1-D data is further processed via correlation processing to detect camera zoom and pan. Working with projection data saves processing time by an order of magnitude, since for instance, a 2-D correlation takes N 2 multiplies per point, however a 1-D correlation takes N multiplies per point. The efficacy of the proposed algorithm is tested for a number of image sequences and the algorithm is shown to be successful in detecting camera motions. The proposed algorithm is expected to be beneficial for video parsers working with Motion-JPEG data stream where motion vectors are not available.

KW - Camera motion detection

KW - Scene change detection

KW - Video library

KW - Video parser

UR - http://www.scopus.com/inward/record.url?scp=0032374234&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032374234&partnerID=8YFLogxK

U2 - 10.1117/12.302417

DO - 10.1117/12.302417

M3 - Conference contribution

AN - SCOPUS:0032374234

VL - 3303

SP - 78

EP - 87

BT - Proceedings of SPIE - The International Society for Optical Engineering

A2 - Sinha, D.

ER -