论文标题
人通过轮廓素描重新识别在适度衣服下的令
Person Re-identification by Contour Sketch under Moderate Clothing Change
论文作者
论文摘要
人重新识别（Re-ID）是跨不同相机视图匹配行人图像的过程，是视觉监视的重要任务。最近已经观察到了重新ID的大量发展，并且大多数现有型号主要取决于颜色外观，并假设行人不会在相机的视野中换衣服。但是，当该人（例如犯罪嫌疑人）改变他/她的衣服，导致大多数现有的方法失败时，在不同时间跟踪一个人时，这种限制可能是一个问题，因为他们很大程度上依靠颜色外观，因此他们倾向于将一个人与他人穿着类似衣服相匹配。在这项工作中，我们称之为服装下的人更改“交叉衣的人re-id”。特别是，我们考虑一个人仅适度地改变衣服作为基于可见光图像解决此问题的首次尝试；也就是说，我们假设一个人穿着类似厚度的衣服，因此，当天气在短时间内不会发生实质性变化时，一个人的形状不会发生重大变化。我们根据人形象的轮廓草图进行跨衣的人重新介绍，以利用人体的形状，而不是颜色信息，以提取适合适度衣服变化的功能。由于缺少用于跨封式人物的大规模数据集，我们贡献了一个新数据集，该数据集由221个身份的33698张图像组成。我们的实验说明了跨衣的人的挑战，并证明了我们提出的方法的有效性。
Person re-identification (re-id), the process of matching pedestrian images across different camera views, is an important task in visual surveillance. Substantial development of re-id has recently been observed, and the majority of existing models are largely dependent on color appearance and assume that pedestrians do not change their clothes across camera views. This limitation, however, can be an issue for re-id when tracking a person at different places and at different time if that person (e.g., a criminal suspect) changes his/her clothes, causing most existing methods to fail, since they are heavily relying on color appearance and thus they are inclined to match a person to another person wearing similar clothes. In this work, we call the person re-id under clothing change the "cross-clothes person re-id". In particular, we consider the case when a person only changes his clothes moderately as a first attempt at solving this problem based on visible light images; that is we assume that a person wears clothes of a similar thickness, and thus the shape of a person would not change significantly when the weather does not change substantially within a short period of time. We perform cross-clothes person re-id based on a contour sketch of person image to take advantage of the shape of the human body instead of color information for extracting features that are robust to moderate clothing change. Due to the lack of a large-scale dataset for cross-clothes person re-id, we contribute a new dataset that consists of 33698 images from 221 identities. Our experiments illustrate the challenges of cross-clothes person re-id and demonstrate the effectiveness of our proposed method.
