Reconstruction of B-spline curves and surfaces by adaptive group testing

摘要: Point clouds as measurements of 3D sensors have many applications in various fields such object modeling, environment mapping and surface representation. Storage processing raw point is time consuming computationally expensive. In addition, their high dimensionality shall be considered, which results the well known curse dimensionality. Conventional methods either apply reduction or approximation to captured order make data tractable. B-spline curves surfaces can effectively represent 2D points for most applications. Since all available curve fitting not efficient, based on Group Testing theory an algorithm developed that finds salient sequentially. The models are updated by adding a new process iteratively until Akaike Information Criterion (AIC) met. Also, it has been proved proposed method unique solution so what defined group testing theory. From experimental applicability performance improvement relation some state-of-the-art methods, may concluded. Adaptive Estimation (B-AGE) proposed.B-AGE derives estimation only from points.The found sequentially means testing.B-AGE with minimum Criteria value.