Lag Camera: A Moving Multi-Camera Array for Scene-Acquisition

Many applications, such as telepresence, virtual reality, and interactive walkthroughs, require a three-dimensional(3D)model of real-world environments. Methods, such as lightfields, geometric reconstruction and computer vision use cameras to acquire visual samples of the environment and construct a model. Unfortunately, obtaining models of real-world locations is a challenging task. In particular, important environments are often actively in use, containing moving objects, such as people entering and leaving the scene. The methods previously listed have difficulty in capturing the color and structure of the environment while in the presence of moving and temporary occluders. We describe a class of cameras called lag cameras. The main concept is to generalize a camera to take samples over space and time. Such a camera, can easily and interactively detect moving objects while continuously moving through the environment. Moreover, since both the lag camera and occluder are moving, the scene behind the occluder is captured by the lag camera even from viewpoints where the occluder lies in between the lag camera and the hidden scene. We demonstrate an implementation of a lag camera, complete with analysis and captured environments.

Reflectance Transfer for Material Editing and Relighting

We present a new approach to diffuse reflectance estimation for dynamic scenes. Non-parametric image statistics are used to transfer reflectance properties from a static example set to a dynamic image sequence. The approach allows diffuse reflectance estimation for surface materials with inhomogeneous appearance, such as those which commonly occur with patterned or textured clothing. Material editing is also possible by transferring edited reflectance properties. Material reflectance properties are initially estimated from static images of the subject under multiple directional illuminations using photometric stereo. The estimated reflectance together with the corresponding image under uniform ambient illumination form a prior set of reference material observations. Material reflectance properties are then estimated for video sequences of a moving person captured under uniform ambient illumination by matching the observed local image statistics to the reference observations. Results demonstrate that the transfer of reflectance properties enables estimation of the dynamic surface normals and subsequent relighting combined with material editing. This approach overcomes limitations of previous work on material transfer and relighting of dynamic scenes which was limited to surfaces with regions of homogeneous reflectance. We evaluate our approach for relighting 3D model sequences reconstructed from multiple view video. Comparison to previous model relighting demonstrates improved reproduction of detailed texture and shape dynamics.

CAD Files and European Design Law

Three-dimensional printing (“3DP”) is an additive manufacturing technology that starts with a virtual 3D model of the object to be printed, the so-called Computer-Aided-Design (“CAD”) file. This file, when sent to the printer, gives instructions to the device on how to build the object layer-by-layer. This paper explores whether design protection is available under the current European regulatory framework for designs that are computer-created by means of CAD software, and, if so, under what circumstances. The key point is whether the appearance of a product, embedded in a CAD file, could be regarded as a protectable element under existing legislation. To this end, it begins with an inquiry into the concepts of “design” and “product”, set forth in Article 3 of the Community Design Regulation No. 6/2002 (“CDR”). Then, it considers the EUIPO’s practice of accepting 3D digital representations of designs. The enquiry goes on to illustrate the implications that the making of a CAD file available online might have. It suggests that the act of uploading a CAD file onto a 3D printing platform may be tantamount to a disclosure for the purposes of triggering unregistered design protection, and for appraising the state of the prior art. It also argues that, when measuring the individual character requirement, the notion of “informed user” and “the designer’s degree of freedom” may need to be reconsidered in the future. The following part touches on the exceptions to design protection, with a special focus on the repairs clause set forth in Article 110 CDR. The concluding part explores different measures that may be implemented to prohibit the unauthorised creation and sharing of CAD files embedding design-protected products.

Algorithms For Automatic And Robust Registration Of 3D Head Scans

wo methods for registering laser-scans of human heads and transforming them to a new semantically consistent topology defined by a user-provided template mesh are described. Both algorithms are stated within the Iterative Closest Point framework. The first method is based on finding landmark correspondences by iteratively registering the vicinity of a landmark with a re-weighted error function. Thin-plate spline interpolation is then used to deform the template mesh and finally the scan is resampled in the topology of the deformed template. The second algorithm employs a morphable shape model, which can be computed from a database of laser-scans using the first algorithm. It directly optimizes pose and shape of the morphable model. The use of the algorithm with PCA mixture models, where the shape is split up into regions each described by an individual subspace, is addressed. Mixture models require either blending or regularization strategies, both of which are described in detail. For both algorithms, strategies for filling in missing geometry for incomplete laser-scans are described. While an interpolation-based approach can be used to fill in small or smooth regions, the model-driven algorithm is capable of fitting a plausible complete head mesh to arbitrarily small geometry, which is known as "shape completion". The importance of regularization in the case of extreme shape completion is shown.