Person Re-identification by Contour Sketch under Moderate Clothing Change

Abstract

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.

To appear in TPAMI

References in corpus (5)

• Very Deep Convolutional Networks for Large-Scale Image Recognition
• Rethinking Atrous Convolution for Semantic Image Segmentation
• Person Re-Identification by Camera Correlation Aware Feature Augmentation
• Unsupervised Person Re-identification by Deep Asymmetric Metric Embedding
• Robust Depth-based Person Re-identification

Cited by in corpus (5)

• Semantic-guided Pixel Sampling for Cloth-Changing Person Re-identification
• Sampling Agnostic Feature Representation for Long-Term Person Re-identification
• Exploring Shape Embedding for Cloth-Changing Person Re-Identification via 2D-3D Correspondences
• Discriminative Pedestrian Features and Gated Channel Attention for Clothes-Changing Person Re-Identification
• Multigranular Visual-Semantic Embedding for Cloth-Changing Person Re-identification