It is common to view people in real applications walking in arbitrary directions, holding items, or wearing heavy coats. These factors are challenges in gait-based application methods because they significantly change a person's appearance. This paper proposes a novel method for classifying human gender in real time using gait information. The use of an average gait image (AGI), rather than a gait energy image (GEI), allows this method to be computationally efficient and robust against view changes. A viewpoint (VP) model is created for automatically determining the viewing angle during the testing phase. A distance signal (DS) model is constructed to remove any areas with an attachment (carried items, worn coats) from a silhouette to reduce the interference in the resulting classification. Finally, the human gender is classified using multiple view-dependent classifiers trained using a support vector machine. Experiment results confirm that the proposed method achieves a high accuracy of 98.8 on the CASIA Dataset B and outperforms the recent state-of-the-art methods.
The sex of human walkers can be recognized without familiarity cues from displays of pointlight sources mounted on major joints. Static versions of these abstract displays do not permit accurate recognition of sex. Variation in the degree of armswing or in walking speed generally interferes with recognition, except that faster speeds are associated somewhat with improved recognition of females. Lights on upper-body joints permit more accurate guesses than do Lights on lower-body joints, but identification is possible even from minimal displays, with lights placed only on the ankles. No feedback was given to observers. Confidence judgments of sex relate to the accuracy of responses in a manner that suggests that viewers know what they are doing. Several temporal and spatial factors affect gender recognition of a walker when portrayed, without familiarity cues, as a dynamic point-light display. We demonstrate that, among temporal parameters, the duration of the dynamic stimulus must be longer than 1.6 sec, but that 2.7 sec is fully adequate. Given the speed of our walkers, the recognition threshold appears to be roughly two step cycles. In addition, presentation rate of the stimulus must be near to normal, perhaps because nonnormal rates alter apparent gravity and obscure the normal relationship between output and conservation of energy. We demonstrate that, among spatial factors, the discreteness of the joint information must be maintained for accurate recognition. We go on to argue that it is the information about the shoulder and the hip of a walker that is of primary importance. Finally, inversion of the stimulus display produces the unexpected effect of reversing the apparent sex of most walkers. That is, when presented upside down, male walkers appear female and female walkers appear male.