Individual tree biomass is the basis of retrieving large-scale forest biomass by remote sensing. In order to improve the accuracy and efficiency of forest individual tree biomass estimation, the individual tree biomass of Eucalyptus and Masson pine was accurately estimated by UAV LiDAR point cloud. Firstly, the tree height and crown width are extracted by the optimization algorithm, then the crown area and volume are calculated by the improved convex hull algorithm, and the parameters of individual tree structure are introduced into CAR model to build individual tree biomass estimation model, which is compared with the linear model. The results showed that: (1) The correlation coefficients R2 of height and crown width of Eucalyptus plots were 0.92 and 0.72, respectively; The correlation coefficient R2 of Masson pine plot is 0.94 and 0.78, respectively. The tree parameters extracted by the algorithm have a good correlation with the measured data. (2) The accuracy of the improved CAR model is better than that of the linear model, with R2 of Eucalyptus and Masson pine plots being 0.821 and 0.830, RMSE being 17.731 and 19.149 kg/tree, respectively. (3) The CAR model introduces canopy factors such as canopy area and volume, and the biomass model has better fitting degree and higher accuracy, among which R2 of Eucalyptus and Masson pine plots increased by 0.102 and 0.115, and RMSE decreased by 4.484 and 5.683 kg/tree. Using UAV LiDAR data to extract parameters of individual tree structure for biomass estimation can obtain good goodness of fit and accuracy.