Joint tracking and classification of extended targets with complex shapes

This paper addresses the problem of joint tracking and classification(JTC) of a single extended target with a complex shape. To describe this complex shape, the spatial extent state is first modeled by star-convex shape via a random hypersurface model(RHM), and then used as feature information for target classification. The target state is modeled by two vectors to alleviate the influence of the high-dimensional state space and the severely nonlinear observation model on target state estimation, while the Euclidean distance metric of the normalized Fourier descriptors is applied to obtain the analytical solution of the updated class probability. Consequently, the resulting method is called the "JTC-RHM method." Besides, the proposed JTC-RHM is integrated into a Bernoulli filter framework to solve the JTC of a single extended target in the presence of detection uncertainty and clutter, resulting in a JTC-RHM-Ber filter. Specifically, the recursive expressions of this filter are derived. Simulations indicate that:(1) the proposed JTC-RHM method can classify the targets with complex shapes and similar sizes more correctly, compared with the JTC method based on the random matrix model,(2) the proposed method performs better in target state estimation than the star-convex RHM based extended target tracking method,(3) the proposed JTC-RHM-Ber filter has a promising performance in state detection and estimation, and can achieve target classification correctly.

Experimental analysis of operational data for roundabouts through advanced image processing

Roundabout is still the focus of several investigations due to the relevant number of variables affecting their operational performances(i.e.,capacity,safety,emissions).To develop reliable models,investigations should be supported by devices and relate d sensors to extract variables of interest(i.e.,flow,speed,gap,lag,follow-up time,vehicle classification and trajectory).Notwithstanding that several sensors and technolo gies are currently used for data collection,most of them present limitations.The paper presents the investigation carried out to survey vehicle movem ents at roundabouts as a comprehensive video image analysis system is able to derive the origin/destination(O/D)matrix,compile a vehicle classification,track individual vehicle trajectories together with corresponding speeds and accelerations along paths.To this end,the authors collected video-sequences that were analysed with a piece of software developed for that task.To minimize the problems due to perspective distortion,environmental effects,and obstructions,a number of camera set-up configurations were adopted with equipment being placed on central or external poles,and on permanent fixtures such as raised working platforms outside the confines of the intersection area.Performance of those installation set-ups with different vehicle tracking strategies has been evaluated.Particularly,speed has been successfully related to trajectory tortuosity,the result of which emphasizes the tremendous potential of image analysis and opens up to further studies on the evaluation of the operational effects of roundabout geometrics.