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Proceedings Paper

Exterior and interior shot classification for automatic content-based video indexing
Author(s): Mohsen Ardebilian Fard; Walid Mahdi; Liming Chen
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Paper Abstract

Scene segmentation within a video is an important issue for easy and fast content-based access to on-line video database. In this paper, we introduce the classification of shots into 'Exterior shots' as a new clue with the aim to perform automatic scene segmentation within a video. Indeed, shots taking place outside or inside is a crucial information in the film grammar. Based on luminance intensity variation caused by the natural and artificial lights, our method detects and distinguishes exterior and interior shots. Our technique follows two steps. First, the luminance intensity of every image pixel is calculated by applying a linear image transformation from the CIE 3D color solid spaces RGB to the NTSC 3D perceptual chromaticity coordinates YIQ; we then analyze the maximum of minimum of luminance intensity values from a mosaic version of the image, leading to classify interior and exterior shots. Experimentation we have drawn so far shows that our technique leads to a successful classification rate up to 95 percent. The further work we have been undertaking shows that our method can also distinguish day and night lights within images. These techniques are being used for automatic scene generation within a video.

Paper Details

Date Published: 24 August 1999
PDF: 10 pages
Proc. SPIE 3846, Multimedia Storage and Archiving Systems IV, (24 August 1999); doi: 10.1117/12.360454
Show Author Affiliations
Mohsen Ardebilian Fard, Univ. de Technologie de Compiegne (France)
Walid Mahdi, Ecole Centrale de Lyon (France)
Liming Chen, Ecole Centrale de Lyon (Canada)


Published in SPIE Proceedings Vol. 3846:
Multimedia Storage and Archiving Systems IV
Sethuraman Panchanathan; Shih-Fu Chang; C.-C. Jay Kuo, Editor(s)

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