3D Mixed Invariant and its Application on Object Classification

in IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007 (2007, April)

3D Modelling of bored tunnels

in Brinkgreve (Ed.) Proc. Int. Symposium Beyond 2000 in Computational Geotechnics (1999)

3D Object Recognition Using Fully Intrinsic Skeletal Graphs

in International Conference on Computational Imaging, 2008 (2008, February)

3D organotypic HepaRG cultures as in vitro model for acute and repeated dose toxicity studies.

in Toxicology in vitro : an international journal published in association with BIBRA (2014), 28(1), 104-12

Predictive in vitro models alternative to in vivo animal will have a significant impact in toxicology. Conventional 2D models do not reflect the complexity of a 3D organ resulting in discrepancies between ... [more ▼]

Predictive in vitro models alternative to in vivo animal will have a significant impact in toxicology. Conventional 2D models do not reflect the complexity of a 3D organ resulting in discrepancies between experimental in vitro and in vivo data. Using 3D HepaRG organotypic cultures we tested four drugs (aflatoxin B1, amiodarone, valproic acid and chlorpromazine) for toxic effects and compared the results with 2D HepaRG and HepG2 cultures. We show that 3D HepaRG cultures are more sensitive than the other tested cultures to aflatoxin B1 which is only toxic upon metabolic activation in the liver. We observed that CYP3A4 activity is higher in the 3D HepaRG cultures compared to the 2D HepaRG cultures. Furthermore, we investigated repeated dose toxicity of chlorpromazine and assessed its effects on glucose and lactate metabolism. Sub-toxic concentrations of chlorpromazine induced significant metabolic changes in both 2D and 3D HepaRG cultures upon acute and repeated dose (3 doses) exposure. In summary, our data support the hypothesis that 3D cell culture models better mimic the in vivo tissue and improve cellular functionality. The 3D HepaRG organotypic cultures represent a high throughput system for drug toxicity screening. This system is therefore a promising tool in preclinical testing of human relevance which can allow reducing and/or replacing animal testing for drug adverse effects. [less ▲]

3D Printing: The Next 5 years by Claude Wolf – Into the Future engineered by the Zs

E-print/Working paper (2017)

3D Printing: The Next 5 years by Claude Wolf – Into the Future engineered by the Zs The future of 3D Printing or Additive Manufacturing [AM] will be driven by the next generation of engineers who are just ... [more ▼]

3D Printing: The Next 5 years by Claude Wolf – Into the Future engineered by the Zs The future of 3D Printing or Additive Manufacturing [AM] will be driven by the next generation of engineers who are just about to qualify, the Z generation (1994-2010). Do we, educators, know this Z generation? Do we know what motivates them? The Z generation is a generation of digital natives interacting with PCs, iPads, smartphones and the internet since birth, a pragmatic and short term orientated generation. Our prejudice brands them as unprepared and unmotivated, with their 10 second attention spans, but in reality, they have already proven they are creative, determined and hardworking as well as team oriented, when they are given the opportunity. They have understood that 3D printing offers them this opportunity. [less ▲]

3D Reconstruction and Registration in Medical Endoscopy

Report (2010)

3D Skeleton based Head Detection and Tracking using Range Images

in IEEE Transactions on Vehicular Technology (2009), 58(8), 4064-4077

Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the ... [more ▼]

Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the development of a topology-based framework using a 3-D skeletal model for the robust detection and tracking of a vehicle occupant's head position from low-resolution range image data for a passive safety system. Unlike previous approaches to head detection, the proposed approach explores the topology information of a scene to detect the position of the head. Among the different available topology representations, the Reeb graph technique is chosen and is adapted to low-resolution 3-D range images. Invariance of the graph under rotations is achieved by using a Morse radial distance function. To cope with the particular challenges such as the noise and the large variations in the density of the data, a voxel neighborhood connectivity notion is proposed. A multiple-hypothesis tracker (MHT) with nearest-neighbor data association and Kalman filter prediction is applied on the endpoints of the Reeb graph to select and filter the correct head candidate out of Reeb graph endpoints. A systematic evaluation of the head detection framework is carried out on full-scale experimental 3-D range images and compared with the ground truth. It is shown that the Reeb graph topology algorithm developed herein allows the correct detection of the head of the occupant with only two head candidates as input to the MHT. Results of the experiments demonstrate that the proposed framework is robust under the large variations of the scene. The processing requirements of the proposed approach are discussed. It is shown that the number of operations is rather low and that real-time processing requirements can be met with the proposed method. [less ▲]

3D Time-Of-Flight Camera System and Position/Orientation Calibration Method Therefor

Patent (2011)

3D visualization of archaeological uncertainty

in Proc. ACM Symposium on Applied Perception (2010)

By uncertainty, we define an archaeological expert's level of confidence in an interpretation deriving from gathered evidence. Archaeologists and computer scientists have urged caution in the use of 3D ... [more ▼]

By uncertainty, we define an archaeological expert's level of confidence in an interpretation deriving from gathered evidence. Archaeologists and computer scientists have urged caution in the use of 3D for archaeological reconstructions because the availability of other possible hypotheses is not always being acknowledged. This poster presents a 3D visualization system of archaeological uncertainty. [less ▲]

3DBodyTex: Textured 3D Body Dataset

in 2018 Sixth International Conference on 3D Vision (3DV 2018) (2018)

In this paper, a dataset, named 3DBodyTex, of static 3D body scans with high-quality texture information is presented along with a fully automatic method for body model fitting to a 3D scan. 3D shape ... [more ▼]

In this paper, a dataset, named 3DBodyTex, of static 3D body scans with high-quality texture information is presented along with a fully automatic method for body model fitting to a 3D scan. 3D shape modelling is a fundamental area of computer vision that has a wide range of applications in the industry. It is becoming even more important as 3D sensing technologies are entering consumer devices such as smartphones. As the main output of these sensors is the 3D shape, many methods rely on this information alone. The 3D shape information is, however, very high dimensional and leads to models that must handle many degrees of freedom from limited information. Coupling texture and 3D shape alleviates this burden, as the texture of 3D objects is complementary to their shape. Unfortunately, high-quality texture content is lacking from commonly available datasets, and in particular in datasets of 3D body scans. The proposed 3DBodyTex dataset aims to fill this gap with hundreds of high-quality 3D body scans with high-resolution texture. Moreover, a novel fully automatic pipeline to fit a body model to a 3D scan is proposed. It includes a robust 3D landmark estimator that takes advantage of the high-resolution texture of 3DBodyTex. The pipeline is applied to the scans, and the results are reported and discussed, showcasing the diversity of the features in the dataset. [less ▲]