Finding Regions of Interest in Home Videos Based on Camera Motion

Get BibTex-formatted data

Download

PDF

Author

G Abdollahian, EJ Delp

Entry type

article

Abstract

In this paper, we propose an algorithm for identifying regions of interest (ROIs) in video, particularly for the keyframes extracted from a home video. The camera motion is introduced as a new factor that can influence the visual saliency. The global motion parameters are used to generate location-based importance maps. These maps can be combined with other saliency maps calculated using other visual and high-level features. Here, we employed the contrast-based saliency as an important low level factor along with face detection as a high level feature in our approach.

Download

PDF

Date

2007

Journal

Image Processing, 2007. ICIP 2007. IEEE International Conference on

Key alpha

Delp

Pages

545-548

Volume

Publication Date

2007-01-01

Keywords

home computing, image motion analysis, video cameras, video retrieval, video signal processingROI, camera motion, contrast-based saliency, home videos, location-based importance map, regions-of-interest identification

BibTex-formatted data

To refer to this entry, you may select and copy the text below and paste it into your BibTex document. Note that the text may not contain all macros that BibTex supports.

@Article{ Delp,
	title = "Finding Regions of Interest in Home Videos Based on Camera Motion",
	author = "G Abdollahian, EJ Delp   ",
	year = "2007",
	journal = "Image Processing, 2007. ICIP 2007. IEEE International Conference on",
	pages = "545-548",
	volume = "4",
	abstract = "In this paper, we propose an algorithm for identifying regions of interest (ROIs) in video, particularly for the keyframes extracted from a home video. The camera motion is introduced as a new factor that can influence the visual saliency. The global motion parameters are used to generate location-based importance maps. These maps can be combined with other saliency maps calculated using other visual and high-level features. Here, we employed the contrast-based saliency as an important low level factor along with face detection as a high level feature in our approach.",
	keywords = "home computing, image motion analysis, video cameras, video retrieval, video signal processingROI, camera motion, contrast-based saliency, home videos, location-based importance map, regions-of-interest identification",
}