Development of Local Government Watching Technology Using Gait Recognition Robust to Occlusion

Abstract

In Japan, the proportion of the elderly person exceeds 25% in 2015 and continues to increase. Then, the number of missing elderly due to dementia is also increasing. Many local governments are supporting the early detection by establishing watching service. However, further early detection is necessary because it takes time to detect by manual search based on pre-registered information on physical characteristics. Therefore, we aim to develop a technology that supports the early detection and notification to the searcher of the watching service by automatically detecting the target person from multiple surveillance cameras based on their pre-registered gait information when searching. Since occlusion caused by the static objects such as guardrails occurs in the surveillance camera images, it is necessary to develop a collation algorithm robust to occlusion. In this paper, we evaluated the accuracy of previous methods using face, whole-body and gait information. In addition, we propose a gait recognition that enables high accuracy by adaptively selecting features according to occlusion. As a result of evaluation using originally made occlusion images, the proposed method achieved the highest accuracy with an average of 83.4%. We will aim at the practical application by evaluating with the actual surveillance camera images.