An In-Car Objects Detection Algorithm Based on Improved Spatial-Temporal Entropy Image
Xiangping Gao, Chao Zhang, Haoqi Duan · 2020
Most of the existing vehicle-loaded video surveillance systems aim at recoding and analyzing the outer circumstance of the vehicles. The inside drivers' and passengers' motion and status, however, are also greatly related to vehicles' running safety. In this paper, we combined Spatial-Temporal Entropy Image (STEI) with Independent Component Analysis (ICA) to deal with in-vehicle scenes, which are usually contain dynamic background and subtle motions. The entropy which denotes the temporal discrimination of local areas is computed. Meanwhile, the short-term accumulation of the independent dynamic component is subtracted to extract drivers and passengers from an in-vehicle scene. The quantitative evaluation from experimental results show that the improved STEI achieves a better detection performance with a reasonable cost of tiny increase on false alarms.