OBJECTIVE: Motorized vehicles (MV) and non-motorized vehicles (NMV) are mixed in the intersection center area (ICA). This mixing leads to complicated interactions between vehicles, which seriously affects traffic safety, especially at mixed intersections of high density. To deep understanding of the interaction course between motorized and non-motorized vehicles in ICAs. METHODS: Two intersections with a high density of interaction behavior between motorized and non-motorized vehicles were investigated through high-resolution traffic video. Firstly, to extract high-precision trajectories from roadside video, we proposed a new trajectory extraction framework that integrates Yolov7, Deepsort, and the trajectory reconstruction algorithm, which integrated the social force model and particle filtering (SFPF) proposed in our previous research. Second, 183 complete interaction events between motorized and non-motorized vehicles were extracted based on the surrogate safety indicator TTC, and latent variables affecting the course of interaction behavior between motorized and non-motorized vehicles were defined based on turning direction, kinetic state, surrounding environment, signal light, vehicle action behavior, and types of NMV. Third, an ordered logit model was built to study the interactions. RESULTS: Analyzing the significance of the model showed that the following variables have a significant effect on the severity of the conflict ( CONCLUSIONS: The study contributes to developing active safety control and driver assistance strategies.