New 3D Projection Transformation for Point Clouds

3D Computer Graphics based on clouds of points is an alternative of interest for high quality rendering of complex scenes. For high quality graphics, the computational requirements are significantly higher than in the case of conventional front-end vertex processing. One of the key computations in the graphics pipeline is the projection transformation. Conventional computation of the point-based projection using current vertex processors might not be the best option for scalable, high quality 3D graphics based on point clouds. In this work we propose a new scalable method that takes advantage of the special characteristics of the point rendering model. The number of reciprocal/division computations for perspective correction is reduced, using instead more effective multiply-accumulate operations. This is done by performing a linear approximation of the reciprocal at the cost of introducing an error in the pixel value. There is a trade-off in the error introduced and the exactness of the computation (linear approximation instead of reciprocal).