In [3], a low-resolution range sensor was investigated for an occupant classification system that distinguish person from child seats or an empty seat. The optimal deployment of vehicle airbags for maximum protection moreover requires information about the occupant's size and position. The detection of occupant's position involves the detection and localization of occupant's head. This is a challenging problem as the approaches based on local shape analysis (in 2D or 3D) alone are not robust enough as other parts of the person's body like shoulders, knee may have similar shapes as the head. This paper discusses and investigate the potential of a Reeb graph approach to describe the topology of vehicle occupants in terms of a skeleton. The essence of the proposed approach is that an occupant sitting in a vehicle has a typical topology which leads to different branches of a Reeb Graph and the possible location of the occupant's head are thus the end points of the Reeb graph. The proposed method is applied on real 3D range images and is compared to Ground truth information. Results show the feasibility of using topological information to identify the position of occupant's