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Scene Understanding in Images

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Intelligent Systems Technologies and Applications 2016 (ISTA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 530))

Abstract

Scene understanding targets on the automatic identification of thoughts, opinion, emotions, and sentiment of the scene with polarity. The sole aim of scene understanding is to build a system which infer and understand the image or a video just like how humans do. In the paper, we propose two algorithms- Eigenfaces and Bezier Curve based algorithms for scene understanding in images. The work focuses on a group of people and thus, targets to perceive the sentiment of the group. The proposed algorithm consist of three different phases. In the first phase, face detection is performed. In the second phase, sentiment of each person in the image is identified and are combined to identify the overall sentiment in the third phase. Experimental results show Bezier curve approach gives better performance than Eigenfaces approach in recognizing the sentiments in multiple faces.

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Correspondence to S Athira .

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© 2016 Springer International Publishing AG

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Athira, S., Manjusha, R., Parameswaran, L. (2016). Scene Understanding in Images. In: Corchado Rodriguez, J., Mitra, S., Thampi, S., El-Alfy, ES. (eds) Intelligent Systems Technologies and Applications 2016. ISTA 2016. Advances in Intelligent Systems and Computing, vol 530. Springer, Cham. https://doi.org/10.1007/978-3-319-47952-1_20

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  • DOI: https://doi.org/10.1007/978-3-319-47952-1_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47951-4

  • Online ISBN: 978-3-319-47952-1

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