  Surveillance based on Computer Vision has become a major necessity in current
era. Most of the surveillance systems operate on visible light imaging, but
performance based on visible light imaging is limited due to some factors like
variation in light intensity during the daytime. The matter of concern lies in
the need for processing images in low light, such as in the need of nighttime
surveillance. In this paper, we have proposed a novel approach for human
detection using FLIR(Forward Looking Infrared) camera. As the principle
involves sensing based on thermal radiation in the Near IR Region, it is
possible to detect Humans from an image captured using a FLIR camera even in
low light. The proposed method for human detection involves processing of
Thermal images by using HOG (Histogram of Oriented Gradients) feature
extraction technique along with some enhancements. The principle of the
proposed technique lies in an adaptive background subtraction algorithm, which
works in association with the HOG technique. By means of this method, we are
able to reduce execution time, precision and some other parameters, which
result in improvement of overall accuracy of the human detection system.
