CASIA-B

该数据集名为CASIA-B，包含了来自124个受试者在11个不同视角下，三种行走状态（正常行走、背包行走和穿大衣行走）的步态数据。该数据集被用于评估所提出的iLGaCo增量学习方法，重点关注添加新的视角和行走状态。其规模涵盖了124名受试者、11个视角角度以及3种行走条件，任务是对步态进行识别。

The dataset named CASIA-B contains gait data from 124 subjects, with coverage of 11 distinct viewpoints and three walking conditions: normal walking, walking with a backpack, and walking while wearing a coat. This dataset is employed to evaluate the proposed iLGaCo incremental learning approach, with a key focus on scenarios where new viewpoints and walking conditions are added. Spanning 124 subjects, 11 viewpoint angles and three walking conditions, the dataset is designed for the task of gait recognition.