Abstract. Regular expressions and the associated regular algebra provide a rich formalism for specifying and analysing sequential models of computation. For parallel computation, extensions to handle twodimensional patterns are often required. In this paper we present a new type of regular expressions for two-dimensional patterns based on contours and their composition. Targeted applications comes from the area of modelling, specification, analysis and verification of structured interactive programs via the associated scenario semantics.

It is difficult to perform 3D reconstruction from on-vehicle gathered video due to the large forward motion of the vehicle. Even object detection and human sensing models perform significantly worse on onboard videos when compared to standard benchmarks because objects often appear far away from the camera compared to the standard object detection benchmarks, image quality is often decreased by motion blur and occlusions occur often. This has led to the popularisation of traffic data-specific benchmarks. Recently Light Detection And Ranging (LiDAR) sensors have become popular to directly estimate depths without the need to perform 3D reconstructions. However, LiDAR-based methods still lack in articulated human detection at a distance when compared to image-based methods. We hypothesize that benchmarks targeted at articulated human sensing from LiDAR data could bring about increased research in human sensing and prediction in traffic and could lead to improved traffic safety for pedestrians.

No abstract

No abstract