This paper describes a large-scale gait database comprising the Treadmill Dataset. The dataset focuses on variations in walking conditions and includes 200 subjects with 25 views, 34 subjects with 9 speed variations from 2 km/h to 10 km/h with a 1 km/h interval, and 68 subjects with at most 32 clothes variations. The range of variations in these three factors is significantly larger than that of previous gait databases, and therefore, the Treadmill Dataset can be used in research on invariant gait recognition. Moreover, the dataset contains more diverse gender and ages than the existing databases and hence it enables us to evaluate gait-based gender and age group classification in more statistically reliable way.
High Dynamic Range Images (HDRIs) are needed for capturing scenes that include drastic lighting changes. This paper presents a method to improve the dynamic range of a camera by using a reflective liquid crystal. The system consists of a camera and a reflective liquid crystal placed in front of the camera. By controlling the attenuation rate of the liquid crystal, the scene radiance for each pixel is adaptively controlled. After the control, the original scene radiance is derived from the attenuation rate of the liquid crystal and the radiance obtained by the camera. A prototype system has been developed and tested for a scene that includes drastic lighting changes. The radiance of each pixel was independently controlled and the HDRIs were obtained by calculating the original scene radiance from these results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.