In this paper we present a novel method for detecting humans from laser range scans, where the core idea is to treat neither individual frames, which hold so little information that the task is impossible, nor motion patterns, as is the case with tracking methods. Rather, we map short time series of planar scans to 3D objects with time as the depth dimension; we then cluster and classify these ...

This article presents a holistic approach to the surface-based segmentation of 3D range data. The proposed framework is generic and requires only that i) the data be dense enough to allow for normal vector estimation and ii) the view point be known for every point in the data set. In contrast to many previous works on segmentation that consider only a few unoccluded and densely sampled objects,...

A range query applies an aggregation operation (e.g., SUM) over all selected cells of an OLAP data cube where the selection is speci®ed by providing ranges of values for numeric dimensions. Range sum queries on data cubes are a powerful analysis tool. Many application domains require that data cubes are updated often and the information provided by analysis tools are current or ``near current''...

We introduce a data processing pipeline designed to generate registration markers from range scan data. This approach uses curvature maps and histogram-templates to identify local surface features. The noise associated with real-world scans is addressed using a (common) Gauss filter and expansion-segmentation. Experimental results are presented for data from The Digital Michelangelo Project.

This thesis describes the design, implementation and application of an integrated and fully automated system for interpreting whole-body range data. The system is shown to be capable of generating complete surface models of human bodies, and robustly extracting anatomical features for anthropometry, with minimal intrusion on the subject. The ability to automate this process has enormous potenti...

We present a novel approach to reliable and efficient recovery of part-descriptions in terms of superquadric models from range data. We show that superquadrics can directly be recovered from unsegmented data, thus avoiding any presegmentation steps (e.g., in terms of surfaces). The approach is based on the recover-andselect paradigm [10]. We present several experiments on real and synthetic ran...

In this thesis a technique to estimate dynamic processes in range data sequences is developed. This includes the instantaneous velocity field (range flow) of a deformable surface and local expansion rates. For the velocity estimation novel differential constraint equations for the depth and intensity data are introduced. These constraint equations are then combined in a general total least squa...

Post-processing of 3D scanned data is still the bottleneck for a wider diffusion of this technology. In this paper we describe our second generation tools for processing 3D scanned data. In particular, our tools support: range maps alignment, range maps merge (or fusion), mesh simplification and color attribute management. This software package has been implemented by scratch and encompasses bo...

We present a method to compute surface expansion rates from sequences of range data. Towards this end the 3D velocity field (range flow) is extracted first and then used in a second step to estimate the local area expansion. A detailed performance analysis is presented and the method is applied on two real examples.