Exploiting 3D information for an automated semantic analysis of underwater images

利用 3D 信息对水下图像进行自动语义分析

• 批准号: 398534188
• 负责人: Dr. Timm Schoening
• 金额: --
• 依托单位: Centre of IMAR
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2017
• 资助国家: 德国
• 起止时间: 2016-12-31 至 2017-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/398534188?language=en
• 关键词: Exploiting; 3D; information; automated; semantic

Automated image analysis is a common methodology, but has seen little application for underwater imagery. Pattern recognition and machine learning methods are challenged by the peculiar environment. Imaging under water is prone to attenuation, turbidity and varying illumination. Anyhow, several studies have shown success in exploiting 2D information for a semantic interpretation of underwater images. There exist, however, cases where 2D information alone is not sufficient to extract knowledge from the images. In those cases 3D, information could help.Here, an existing 3D data set shall be analysed. It will be complimented by 3D imagery acquired under controlled conditions. Additional morphological information shall be incorporated into automated 2D pattern recognition methods. Joint research with marine biologists will be conducted. Semantic data, automatically extracted from the imagery, will be used for a better spatial understanding of the imaged habitats.

自动图像分析是一种常见的方法，但很少应用于水下图像。模式识别和机器学习方法受到特殊环境的挑战。水下成像易于衰减、浑浊和变化的照明。无论如何，一些研究已经表明，在利用2D信息对水下图像进行语义解释方面取得了成功。然而，存在仅2D信息不足以从图像中提取知识的情况。在这些情况下，3D信息可能会有所帮助。这里，应分析现有的3D数据集。它将得到在受控条件下获得的3D图像的补充。应将额外的形态学信息纳入自动2D模式识别方法。将与海洋生物学家进行联合研究。从图像中自动提取的语义数据将用于更好地从空间上了解成像的生境。