Cell-based approach for 3D reconstruction from incomplete silhouettes

Shape-from-silhouettes is a widely adopted approach to compute accurate 3D reconstructions of people or objects in a multi-camera environment. However, such algorithms are traditionally very sensitive to errors in the silhouettes due to imperfect foreground-background estimation or occluding objects appearing in front of the object of interest. We propose a novel algorithm that is able to still provide high quality reconstruction from incomplete silhouettes. At the core of the method is the partitioning of reconstruction space in cells, i.e. regions with uniform camera and silhouette coverage properties. A set of rules is proposed to iteratively add cells to the reconstruction based on their potential to explain discrepancies between silhouettes in different cameras. Experimental analysis shows significantly improved F1-scores over standard leave-M-out reconstruction techniques

Construction Cost Sensitivity of a Lignocellulosic Ethanol Biorefinery

The technology has been developed to convert feedstock with cellulose content into ethanol. However, ethanol produced from cellulosic feedstock is the same as ethanol distilled from grain. The objective of research is to determine the price per gallon of ethanol needed so that producing lignocellulosic based ethanol become economically feasible.Environmental Economics and Policy, Production Economics,

Parameter-unaware autocalibration for occupancy mapping

People localization and occupancy mapping are common and important tasks for multi-camera systems. In this paper, we present a novel approach to overcome the hurdle of manual extrinsic calibration of the multi-camera system. Our approach is completely parameter unaware, meaning that the user does not need to know the focal length, position or viewing angle in advance, nor will these values be calibrated as such. The only requirement to the multi-camera setup is that the views overlap substantially and are mounted at approximately the same height, requirements that are satisfied in most typical multi-camera configurations. The proposed method uses the observed height of an object or person moving through the space to estimate the distance to the object or person. Using this distance to backproject the lowest point of each detected object, we obtain a rotated and anisotropically scaled view of the ground plane for each camera. An algorithm is presented to estimate the anisotropic scaling parameters and rotation for each camera, after which ground plane positions can be computed up to an isotropic scale factor. Lens distortion is not taken into account. The method is tested in simulation yielding average accuracies within 5cm, and in a real multi-camera environment with an accuracy within 15cm

Self-learning voxel-based multi-camera occlusion maps for 3D reconstruction

The quality of a shape-from-silhouettes 3D reconstruction technique strongly depends on the completeness of the silhouettes from each of the cameras. Static occlusion, due to e.g. furniture, makes reconstruction difficult, as we assume no prior knowledge concerning shape and size of occluding objects in the scene. In this paper we present a self-learning algorithm that is able to build an occlusion map for each camera from a voxel perspective. This information is then used to determine which cameras need to be evaluated when reconstructing the 3D model at every voxel in the scene. We show promising results in a multi-camera setup with seven cameras where the object is significantly better reconstructed compared to the state of the art methods, despite the occluding object in the center of the room

Integer programming methods for large-scale practical classroom assignment problems

In this paper we present an integer programming method for solving the Classroom Assignment Problem in University Course Timetabling. We introduce a novel formulation of the problem which generalises existing models and maintains tractability even for large instances. The model is validated through computational results based on our experiences at the University of Auckland, and on instances from the 2007 International Timetabling Competition. We also expand upon existing results into the computational difficulty of room assignment problems

Broadband Dispersion-Free Optical Cavities Based on Zero Group Delay Dispersion Mirror Sets

A broadband dispersion-free optical cavity using a zero group delay dispersion (zero-GDD) mirror set is demonstrated. In general zero-GDD mirror sets consist of two or more mirrors with opposite group delay dispersion (GDD), that when used together, form an optical cavity with vanishing dispersion over an enhanced bandwidth in comparison with traditional low GDD mirrors. More specifically, in this paper, we show a realization of such a two-mirror cavity, where the mirrors show opposite GDD and simultaneously a mirror reflectivity of 99.2% over 100 nm bandwidth (480 nm - 580 nm).Physic

Study on the effects and incidence of labour taxation; Final Report; Study on behalf of the European Commission, TAXUD; CPB in consortium with: CAPP, CASE, CEPII, ETLA, IFO, IFS, IHS.

This report has been prepared for the project “Study on the effects and incidence of labour taxation”, Specific Contract No. TAXUD/2014/DE/313 implementing the Framework Service Contract No. TAXUD/2010/CC/104 for the provision of economic analysis in the a rea of taxation. We are grateful for the valuable feedback of the steering group and the external reviewers