Far-infrared pedestrian sequence segmentation based on time domain semantics

Shaowu Peng, Zhenju Wang, Qiong Liu, Junying Chen
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Abstract

This paper proposes the generation of a pedestrian ROI region, which is mainly aimed at pedestrian segmentation in far-infrared (FIR) images of in-vehicle systems. Since the FIR image is a grayscale image, the pixel value of the pedestrian is usually higher than the background, so the previous segmentation method is mainly threshold segmentation. However, this method will cause problems due to the uneven brightness of pedestrians caused by pedestrian wear, etc. We propose a new method for generating pedestrian ROI regions, which is based on the combination of image region merging and pixel-intensity vertical projection, and adopts the time domain semantic model to constrain the parameter space. Experiments show that our method has achieved good results in urban scenes.
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基于时域语义的远红外行人序列分割
本文提出了行人感兴趣区域的生成,主要针对车载系统远红外图像中行人的分割问题。由于FIR图像是灰度图像,行人的像素值通常高于背景,所以之前的分割方法主要是阈值分割。但是这种方法会因为行人磨损等原因造成行人亮度不均匀而产生问题。提出了一种基于图像区域合并和像素强度垂直投影相结合的行人感兴趣区域生成方法,并采用时域语义模型对参数空间进行约束。实验表明,该方法在城市场景下取得了较好的效果。
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