Gait-based Recognition for Human Identification using Fuzzy Local Binary Patterns

摘要

With the increasing security breaches nowadays, automated gait recognition has recently received increasing importance in video surveillance technology. In this paper, we propose a method for human identification at distance based on Fuzzy Local Binary Pattern (FLBP). After the Gait Energy Image (GEI) is generated as a spatiotemporal summary of a gait video sequence, a multi-region partitioning is applied and FLBP based features are extracted for each region. We also evaluate the performance under the variation of some factors including viewing angle, clothing and carrying conditions. The experimental work showed that GEI-FLBP with partitioning has remarkably enhanced the identification accuracy.