A unified 2D-3D video scene change detection framework for mobile camera platforms

In this paper, we present a novel scene change detection algorithm for mobile camera platforms. Our approach integrates sparse 3D scene background modelling and dense 2D image background modelling into a unified framework. The 3D scene background modelling identifies inconsistent clusters over time in a set of 3D cloud points as the scene changes. The 2D image background modelling further confirms the scene changes by finding inconsistent appearances in a set of aligned images using the classical MRF background subtraction technique. We evaluate the performance of our proposed system on a number of challenging video datasets obtained from a camera placed on a moving vehicle and the experiments show that our proposed method outperforms previous works in scene change detection, which suggested the feasibility of our approach.

Combining 3D and 2D for less constrained periocular recognition

Periocular recognition has recently become an active topic in biometrics. Typically it uses 2D image data of the periocular region. This paper is the first description of combining 3D shape structure with 2D texture. A simple and effective technique using iterative closest point (ICP) was applied for 3D periocular region matching. It proved its strength for relatively unconstrained eye region capture, and does not require any training. Local binary patterns (LBP) were applied for 2D image based periocular matching. The two modalities were combined at the score-level. This approach was evaluated using the Bosphorus 3D face database, which contains large variations in facial expressions, head poses and occlusions. The rank-1 accuracy achieved from the 3D data (80%) was better than that for 2D (58%), and the best accuracy (83%) was achieved by fusing the two types of data. This suggests that significant improvements to periocular recognition systems could be achieved using the 3D structure information that is now available from small and inexpensive sensors.

Computational analysis of laminated glass panels under blast loads: A comparison of two dimensional and three dimensional modelling approaches

This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.

Application of domain decomposition and transmission line modelling techniques to 2D, time-domain, finite element problems

In this paper a recently published finite element method, which combines domain decomposition with a novel technique for solving nonlinear magnetostatic finite element problems is described. It is then shown how the method can be extended to, and optimised for, the solution of time-domain problems. © 1999 IEEE.

Relative Affine Structure: Canonical Model for 3D from 2D Geometry and Applications

We propose an affine framework for perspective views, captured by a single extremely simple equation based on a viewer-centered invariant we call "relative affine structure". Via a number of corollaries of our main results we show that our framework unifies previous work --- including Euclidean, projective and affine --- in a natural and simple way, and introduces new, extremely simple, algorithms for the tasks of reconstruction from multiple views, recognition by alignment, and certain image coding applications.

2D, 3D and 4D active compound delivery in tissue engineering and regenerative medicine

Recent advances in tissue engineering and regenerative medicine have shown that controlling cells microenvironment during growth is a key element to the development of successful therapeutic system. To achieve such control, researchers have first proposed the use of polymeric scaffolds that were able to support cellular growth and, to a certain extent, favor cell organization and tissue structure. With nowadays availability of a large pool of stem cell lines, such approach has appeared to be rather limited since it does not offer the fine control of the cell micro-environment in space and time (4D). Therefore, researchers are currently focusing their efforts on developing strategies that include active compound delivery systems in order to add a fourth dimension to the design of 3D scaffolds. This review will focus on recent concepts and applications of 2D and 3D techniques that have been used to control the load and release of active compounds used to promote cell differentiation and proliferation in or out of a scaffold. We will first present recent advances in the design of 2D polymeric scaffolds and the different techniques that have been used to deposit molecular cues and cells in a controlled fashion. We will continue presenting the recent advances made in the design of 3D scaffolds based on hydrogels as well as polymeric fibers and we will finish by presenting some of the research avenues that are still to be explored.

Air pressure and wind velocity - modelling ember attack within the urban-rural interface

As population change places pressure on expanding regional and metropolitan urban boundaries, so the threat of bushfire at the rural/urban interface increases. This paper presents a range of 2D and 3D 1:40 and full scale modelling investigations. Various relationships are explored between the urban and rural interface with respect to: air pressure; changes in wind pattern; vectorial velocity; and the deposition of hot ash and firebrand deposits around single story building forms, both as standalone and within an orthogonal array and cul-de-sac relationships.

Marine object detection using background modelling and blob analysis

Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive way via setting up a camera and seeking objects in images is more promising. In this paper, a novel technique of object detection in images is presented, which is applicable to generic objects. A robust background modelling algorithm is proposed to extract foregrounds and then blob features are introduced to classify foregrounds. Particular marine objects, box jellyfish and sea snake, are successfully detected in our work. Experiments conducted on image datasets collected by the Australian Institute of Marine Science (AIMS) demonstrate the effectiveness of the proposed technique.

Gaussian mixture background modelling optimisation for micro-controllers

This paper proposes an optimisation of the adaptive Gaussian mixture background model that allows the deployment of the method on processors with low memory capacity. The effect of the granularity of the Gaussian mean-value and variance in an integer-based implementation is investigated and novel updating rules of the mixture weights are described. Based on the proposed framework, an implementation for a very low power consumption micro-controller is presented. Results show that the proposed method operates in real time on the micro-controller and has similar performance to the original model. © 2012 Springer-Verlag.

Flow due to multiple jets downstream of a barrage: Experiments, 3-D CFD and depth-averaged modelling

The flow through and downstream of a row of seven open draft tubes in a barrage has been investigated through laboratory experiments in a wide flume, a three-dimensional (3D) computational fluid dynamics simulation, and a two-dimensional depth-averaged computation. Agreement between the experiments and the 3D modeling is shown to be good, including the prediction of an asymmetric Coandă effect. One aim is to determine the distance downstream at which depth-averaged modeling provides a reasonable prediction; this is shown to be approximately 20 tube diameters downstream of the barrage. Upstream of this, the depth-averaged modeling inaccurately predicts water level, bed shear, and the 3D flow field. The 3D model shows that bed shear stress can be markedly magnified near the barrage, particularly where the jets become attached.