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Exterior and interior shot classification for automatic content-based video indexing

机译:外部和内部镜头分类,用于基于内容的自动视频索引

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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. !36
机译:摘要:视频中的场景分割是轻松,快速地基于内容访问在线视频数据库的重要问题。在本文中,我们将镜头的分类引入“外部镜头”作为新线索,旨在在视频中执行自动场景分割。实际上,在电影语法中,在外部或内部进行拍摄是至关重要的信息。基于自然光和人造光引起的亮度强度变化,我们的方法可以检测并区分外部和内部镜头。我们的技术遵循两个步骤。首先,通过应用从CIE 3D彩色实心空间RGB到NTSC 3D感知色度坐标YIQ的线性图像变换来计算每个图像像素的亮度强度;然后,然后,我们从图像的马赛克版本中分析亮度强度值的最小值的最大值,从而对内部和外部镜头进行分类。到目前为止,我们进行的实验表明,我们的技术可以成功将分类率提高到95%。我们正在进行的进一步工作表明,我们的方法还可以区分图像中的日夜灯。这些技术正用于视频中的自动场景生成。 !36

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