The industry dealing with microchip inspection requires fast, flexible, repeatable, and stable 3-D measuring systems. The typical devices used for this purpose are coordinate measurement machines (CMMs). These systems have limitations such as high cost, low measurement speed, and small quantity of measured 3-D points. Now optical techniques are beginning to replace the typical touch probes because of their noncontact nature, their full-field measurement capability, their high measurement density, as well as their low cost and high measurement speed. However, typical properties of microchip devices, which include a strongly spatially varying reflectance, make impossible the direct use of the classical optical 3-D measurement techniques. We present a 3-D measurement technique capable of optically measuring these devices using a camera-projector system. The proposed method improves the dynamic range of the imaging system through the use of a set of gray-code (GC) and phase-shift (PS) measures with different CCD integration times. A set of extended-range GC and PS images are obtained and used to acquire a dense 3-D measure of the object. We measure the 3-D shape of an integrated circuit and obtained satisfactory results.
In this paper a new approach to 3D human body tracking is proposed. A
sparse 3D reconstruction of the subject to be tracked is made using a structured light system consisting of a precalibrated LCD projector and a camera. At a number of points-of-interest, easily detectable features are projected. The resulting sparse 3D reconstruction is
used to estimate the body pose of the tracked person. This new estimate of the body pose is then fed back to the structured light system and allows to adapt the projected patterns, i.e. decide where to project features. Given the observations, a physical simulation is used to estimate the body pose by attaching forces to the limbs of the body model. The sparse 3D observations are augmented by denser silhouette information, in order to make the tracking more robust.
Experiments demonstrate the feasibility of the proposed approach and show that the high speeds that are required due to the closed feedback loop can be achieved.
This paper presents a high-speed, single shot range scanner. The depth acquisition is based on classical triangulation, facilitated by structured light. The projection pattern consists of equidistant vertical stripes. The major contribution of our research is that this setup is amenable to real-time processing. Both from an algorithmic and an implementation point of view, the speed constraint is taken into account. The paper discusses both the pattern detection and the camera and projector calibration. The subpixel accurate detection, which is the main computational problem, is implemented as a two-stage algorithm. An initialization procedure yields the rough contours. Subpixel accuracy is reached through an iterative relaxation process. A consistent labeling is assigned based on belief propagation.