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Intelligent vision-based traffic surveillance systems are assuming an increasingly important role in highway monitoring and road management schemes. This paper describes a low-level object tracking system that produces accurate vehicle motion trajectories that can be further analyzed to detect lane centers and classify lane types. Accompanying techniques(More)
A new technique is proposed for clustering and similarity retrieval of video motion clips based on spatio-temporal object trajectories. The trajectories are treated as motion time series and represented either by least squares or Chebyshev polynomial approximations. Trajectory clustering is then carried out to discover patterns of similar object motion(More)
This paper proposes a novel technique for clustering and classification of object trajectory-based video motion clips using spatiotemporal function approximations. Assuming the clusters of trajectory points are distributed normally in the coefficient feature space, we propose a Mahalanobis classifier for the detection of anomalous trajectories. Motion(More)
This paper proposes a novel technique for clustering and classification of object trajectory-based video motion clips using spatiotemporal functional approximations. A Mahalanobis classifier is then used for the detection of anomalous trajectories. Motion trajectories are considered as time series and modeled using the leading Fourier coefficients obtained(More)
Techniques for understanding video object motion activity are becoming increasingly important with the widespread adoption of CCTV surveillance systems. In this paper we propose a novel vision system for clustering and classification of object-based video motion clips using spatiotemporal models. Object trajectories are modeled as motion time series using(More)
This paper describes a comparative evaluation of three different similarity metrics for trajectory-based indexing and retrieval of video motion clips. The motion paths are generated using a low-level tracking algorithm incorporating first-order Kalman filter and colour appearance models. For simple motion paths, a RANSAC approach can be used to generate(More)
In this paper, we present a low-level object tracking system that produces accurate vehicle trajectories and estimates the lane geometry using uncalibrated traffic surveillance cameras. A novel algorithm known as Predictive Trajectory Merge-and-Split (PTMS) has been developed to detect partial or complete occlusions during object motion and hence update the(More)
A tracking system is presented for obtaining accurate vehicle trajectories using uncalibrated traffic surveillance cameras. Techniques for indexing and retrieval of vehicle trajectories and estimation of lane geometry are also presented. An algorithm known as Predictive Trajectory Merge-and-Split (PTMS) is used to detect partial or complete occlusions(More)