The pulse wave signal extracted by the non-contact heart rate detection method for a single feature region of a face video is susceptible to motion and light during the video acquisition process. In order to reduce the interference of motion artifacts and uneven illumination on pulse wave signals, a non-contact heart rate signal extraction method with multiple feature regions combined with fast independent component analysis is proposed in this study. Multi-feature regions are selected through the method of facial feature point algorithm combined with positioning regional center to ensure the stability of the feature regions in the video images. Fast independent component analysis is used to achieve the mutual compensation among the green channel blood volume change pulse signal of the images in the multiple feature regions, reducing the effect of uneven lighting. The experiment is performed on the DEAP data set published abroad. The experimental results show that the method in this study is superior to the existing methods based on independent component analysis and independent vector analysis.