Bedeli Marianna, Geradts Zeno, van Eijk Erwin
University of Amsterdam, Amsterdam, The Netherlands.
Netherlands Forensic Institute (NFI), Den Hague, The Netherlands.
Forensic Sci Res. 2018 Oct 17;3(3):219-229. doi: 10.1080/20961790.2018.1526251. eCollection 2018.
Attribute-based identification systems are essential for forensic investigations because they help in identifying individuals. An item such as clothing is a visual attribute because it can usually be used to describe people. The method proposed in this article aims to identify people based on the visual information derived from their attire. Deep learning is used to train the computer to classify images based on clothing content. We first demonstrate clothing classification using a large scale dataset, where the proposed model performs relatively poorly. Then, we use clothing classification on a dataset containing popular logos and famous brand images. The results show that the model correctly classifies most of the test images with a success rate that is higher than 70%. Finally, we evaluate clothing classification using footage from surveillance cameras. The system performs well on this dataset, labelling 70% of the test images correctly.
基于属性的识别系统对于法医调查至关重要，因为它们有助于识别个体。诸如衣物之类的物品是一种视觉属性，因为它通常可用于描述人。本文提出的方法旨在基于从人们着装中获取的视觉信息来识别个体。深度学习用于训练计算机根据衣物内容对图像进行分类。我们首先使用大规模数据集进行衣物分类，在该数据集中所提出的模型表现相对较差。然后，我们在包含流行标志和著名品牌图像的数据集上进行衣物分类。结果表明，该模型能正确分类大多数测试图像，成功率高于70%。最后，我们使用监控摄像头的 footage 评估衣物分类。该系统在这个数据集上表现良好，正确标记了70%的测试图像。
