Person re-identification (reID) aims at finding the same person in different camera views. In real-world scenarios, it is quite often that the suspect’s appearance is not known while the suspect’s escape route is known. This paper introduces a new person reID setting, where the query includes both the real suspect’s trajectory and several possible suspects. The goal is to identify the actual suspect and retrieve images of the real suspect. Prior work focuses on extracting pedestrians’ discriminative visual features or using spatial-temporal information while neglecting the importance of cross-camera trajectory information. Due to the spatial-temporal consistency, the trajectory and image complement each other and the trajectory is associated with the image data. Therefore, we consider retrieving the suspect’s image based on the trajectory and introducing a Hidden Markov Model based trajectory framework to jointly analyze image data and trajectory information. We evaluate our methods on two datasets containing person images and trajectory information, demonstrating our approach’s effectiveness.

行人重识别 (reID) 旨在在不同的摄像机视图中找到同一个人。在现实世界的场景中，嫌疑人的外貌常常是未知的，而嫌疑人的逃生路线却是已知的。本文介绍了一种新的人员 reID 设置，其中查询包括真实嫌疑人的轨迹和几个可能的嫌疑人。目标是识别实际嫌疑人并检索真正嫌疑人的图像。先前的工作侧重于提取行人的判别视觉特征或使用时空信息，而忽略了跨相机轨迹信息的重要性。由于时空一致性，轨迹与图像相辅相成，轨迹与图像数据相关联。所以，我们考虑根据轨迹检索嫌疑人的图像，并引入基于隐马尔可夫模型的轨迹框架来联合分析图像数据和轨迹信息。我们在包含人物图像和轨迹信息的两个数据集上评估我们的方法，证明了我们方法的有效性。