Left Ventricular Ejection Time (LVET), reflecting the duration from the onset to the end of blood ejection by the left ventricle during each heartbeat, is a critical parameter for measuring cardiac pumping efficiency. Continuous and regular monitoring of LVET is particularly crucial in assessing cardiac health, valvular function, and myocardial contractility. Seismocardiogram (SCG) signals can be utilized for LVET monitoring, as the temporal distance between the aortic valve opening (AO) and aortic valve closure (AC) in SCG signals can accurately depict LVET. This study proposes a novel way to extract LVET from laser speckle videos recorded by a remote camera based on the principle of defocused speckle imaging, thereby enabling non-contact monitoring of LVET. We extract both the low-frequency components of laser speckle motion (LSM-LF), regarded as SCG signals, and the high-frequency components of laser speckle motion (LSM-HF) from recorded videos. We utilize LSM-HF to assist the detection of AO and AC markers in LSM-LF. We validated the effectiveness of our AO and AC detection algorithm on a self-made dataset comprising 21 participants with 9616 SCG cycles. The benchmark shows that the detection accuracy for AO and AC reached 98.16% and 97.94%, respectively, with an mean absolute error of 0.5571 ms for LVET estimation. The results demonstrate that camera-SCG has strong potential for cardiac health monitoring.