There is an increasing interest worldwide in animal detection systems to reduce animal-vehicle collisions. Traditional approaches include building animal crossings, introducing real or virtual fencing, video surveillance and break-the-beam systems. Unlike these approaches, the system described here Large Animal Warning and Detection System (LAWDS) employs a 360˚-scanning radar to monitor a stretch of highway. This provides year-round continuous highway monitoring, even in harsh weather conditions. Innovative analysis and classification techniques enable the system to track large animals (e.g. deer). Low false alarm rate and environmental impact make LAWDS attractive for operational use. LAWDS also distinguishes vehicles from large animals and analyzes highway traffic metrics such as traffic volume and vehicle speeds.
The medial axis transform is valuable for shape representation as it is complete and captures part structure. However, its exact computation for arbitrary 3D models is not feasible. We introduce a novel algorithm to approximate the medial axis of a polyhedron with a dense set of medial points, with a guarantee that each medial point is within a specified tolerance from the medial axis. Given this discrete approximation to the medial axis, we use Damon's work on radial geometry [1] to design a numerical method that recovers surface curvature of the object boundary from the medial axis transform alone. We also show that the number of medial sheets comprising this representation may be significantly reduced without substantially compromising the quality of the reconstruction, to create a more useful part-based representation.
We study the problem of approximating a solid with a union of overlapping spheres. We introduce a method based on medial spheres which, when compared to a state-of-the-art approach, offers more than an order of magnitude speedup and achieves a tighter volumetric approximation of the original mesh, while using fewer spheres. The spheres generated by our method are internal to the object, which permits an exact error analysis and comparison with other sphere approximations. We demonstrate that a tight bounding volume hierarchy of our set of spheres may be constructed using rectangle-swept spheres as bounding volumes. Further, once our spheres are dilated, we show that this hierarchy generally offers superior performance in approximate separation distance tests.
We introduce a novel algorithm to compute a dense sample of points on the medial locus of a polyhedral object, with a guarantee that each medial point is within a specified tolerance from the medial surface. Motivated by Damon's work on the relationship between the differential geometry of the smooth boundary of an object and its medial surface [8], we then develop a computational method by which boundary differential geometry can be recovered directly from this dense medial point cloud. Experimental results on models of varying complexity demonstrate the validity of the approach, with principal curvature values that are consistent with those provided by an alternative method that works directly on the boundary. As such, we demonstrate the richness of a dense medial point cloud as a shape descriptor for 3D data processing.
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