This paper presents BiSe-AIHM, a novel method for heart rate estimation from lip microvessel dynamics in video. The approach integrates BiSeNet, a semantic segmentation algorithm, to accurately track lip regions, followed by absorption fluctuation heartbeat modulation (AIHM) for signal extraction. AIHM utilizes the absorption fluctuation modulation effect (AIFM) to derive heart rate-related signals from the green channel of the segmented lip region. These signals are then analyzed using fourier transform and the average shift histogram (ASH) to determine heart rate. Extensive experiments validate the method’s accuracy and stability, achieving 98.83% accuracy with an RMSE of 0.91 bpm. BiSe-AIHM surpasses traditional contact-based and non-contact methods, offering a low-cost, accessible solution for heart rate monitoring using standard camera equipment. This innovation holds great promise for cardiovascular disease prevention, medical diagnostics, and personal health management.