Yu Shiqi, Tan Tieniu, Huang Kaiqi, Jia Kui, Wu Xinyu
IEEE Trans Image Process. 2009 Aug;18(8):1905-10. doi: 10.1109/TIP.2009.2020535. Epub 2009 May 12.
Gender is an important cue in social activities. In this correspondence, we present a study and analysis of gender classification based on human gait. Psychological experiments were carried out. These experiments showed that humans can recognize gender based on gait information, and that contributions of different body components vary. The prior knowledge extracted from the psychological experiments can be combined with an automatic method to further improve classification accuracy. The proposed method which combines human knowledge achieves higher performance than some other methods, and is even more accurate than human observers. We also present a numerical analysis of the contributions of different human components, which shows that head and hair, back, chest and thigh are more discriminative than other components. We also did challenging cross-race experiments that used Asian gait data to classify the gender of Europeans, and vice versa. Encouraging results were obtained. All the above prove that gait-based gender classification is feasible in controlled environments. In real applications, it still suffers from many difficulties, such as view variation, clothing and shoes changes, or carrying objects. We analyze the difficulties and suggest some possible solutions.
性别是社交活动中的一个重要线索。在本通信中，我们展示了一项基于人类步态的性别分类研究与分析。进行了心理实验。这些实验表明，人类能够基于步态信息识别性别，且不同身体部位的贡献有所不同。从心理实验中提取的先验知识可与一种自动方法相结合，以进一步提高分类准确率。所提出的结合人类知识的方法比其他一些方法具有更高的性能，甚至比人类观察者更准确。我们还对不同人体部位的贡献进行了数值分析，结果表明头部和头发、背部、胸部和大腿比其他部位更具判别力。我们还进行了具有挑战性的跨种族实验，即使用亚洲人的步态数据对欧洲人的性别进行分类，反之亦然。获得了令人鼓舞的结果。以上所有都证明基于步态的性别分类在受控环境中是可行的。在实际应用中，它仍然面临许多困难，如视角变化、服装和鞋子的改变或携带物品等。我们分析了这些困难并提出了一些可能的解决方案。
