Abstract: Reconstruction of 3D temperature fields on the human body surface can provide reliable data for a number of human medical analyses, including diagnoses. Based on the limitations of infrared imaging, such as poor temperature measurement accuracy, insufficient imaging resolution, and poor display effects, the reliability of the 3D temperature field collected using infrared imaging is low. To overcome these problems, we propose a fusion reconstruction method for 3D temperature fields on the human body surface. First, the blackbody temperature measurement and calibration method is used to correct the errors in the temperature measurement results of an infrared thermal imager. Second, contrast enhancement processing is applied. Third, super-resolution processing is used to make the infrared images match the 3D data in terms of spatial resolution. Finally, in the data fusion stage, based on the fact that the target feature points extracted from different images correspond to the same position in the space, the system structure parameters obtained through calibration are corrected. Experimental results demonstrate that the temperature error of the 3D temperature field is less than 0.26℃, the 3D distribution of the temperature field is improved, and the display effect is enhanced.