3D sparse feature model using short baseline stereo and multiple view registration

This paper outlines a methodology to generate a distinctive object representation offline, using short-baseline stereo fundamentals to triangulate highly descriptive object features in multiple pairs of stereo images. A group of sparse 2.5D perspective views are built and the multiple views are then fused into a single sparse 3D model using a common 3D shape registration technique. Having prior knowledge, such as the proposed sparse feature model, is useful when detecting an object and estimating its pose for real-time systems like augmented reality.

A field model for repairing 3D shapes

This paper proposes a field model for repairing 3D shapes constructed from multi-view RGB data. Specifically, we represent a 3D shape in a Markov random field (MRF) in which the geometric information is encoded by random binary variables and the appearance information is retrieved from a set of RGB images captured at multiple viewpoints. The local priors in the MRF model capture the local structures of object shapes and are learnt from 3D shape templates using a convolutional deep belief network. Repairing a 3D shape is formulated as the maximum a posteriori (MAP) estimation in the corresponding MRF. Variational mean field approximation technique is adopted for the MAP estimation. The proposed method was evaluated on both artificial data and real data obtained from reconstruction of practical scenes. Experimental results have shown the robustness and efficiency of the proposed method in repairing noisy and incomplete 3D shapes.

Obtaining functional parametric models using active vision strategies

This paper addresses the problem of determining which 3D shape is present, and more importantly, the dimensions of the shape in a scene. This is performed in an active vision system because it reduces the complexity of the problem through the use of gaze stabilization, choice of foveation point, and selective processing by adaptively processing regions of interest. In our case, only a small number of equations and parameters are needed for each shape and these are incorporated into functional descriptions of the shapes.

Emerging hypothesis verification using function-based geometric models and active vision strategies

This paper describes an investigation into the use of parametric 2D models describing the movement of edges for the determination of possible 3D shape and hence function of an object. An assumption of this research is that the camera can foveate and track particular features. It is argued that simple 2D analytic descriptions of the movement of edges can infer 3D shape while the camera is moved. This uses an advantage of foveation i.e. the problem becomes object centred. The problem of correspondence for numerous edge points is overcome by the use of a tree based representation for the competing hypotheses. Numerous hypothesis are maintained simultaneously and it does not rely on a single kinematic model which assumes constant velocity or acceleration. The numerous advantages of this strategy are described.

Obtaining function models using active vision strategies

This paper addresses the problem of determening which 3D shape is present, and more importantly, the dimensions of the shape within a scene. This is performed in an active vision system because it reduces the complexity of the problem through the use of gaze stabilisation, choice of foveation point and selective processing by adaptively processing regions of interest. In our case only a small number of equations and parameters are needed for each shape. For example, a container has width and height. These are incorporated into functional descriptions of the shapes.

Development and evaluation of an ELISA for the detection and 3D antibodies to foot and mouth disease virus

A group specific ELISA (enzyme-linked immunosorbent assay) was developed to detect virus infection associated antibodies in the serum of animals infected with any serotype of foot and mouth disease virus. The assay was developed from non-infectious sources, and is therefore suitable for use in countries where FMDV is exotic.

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.

3D-printed and CNC milled flow-cells for chemiluminescence detection

Herein we explore modern fabrication techniques for the development of chemiluminescence detection flow-cells with features not attainable using the traditional coiled tubing approach. This includes the first 3D-printed chemiluminescence flow-cells, and a milled flow-cell designed to split the analyte stream into two separate detection zones within the same polymer chip. The flow-cells are compared to conventional detection systems using flow injection analysis (FIA) and high performance liquid chromatography (HPLC), with the fast chemiluminescence reactions of an acidic potassium permanganate reagent with morphine and a series of adrenergic phenolic amines.

2D and 3D modelling of building form subjected to ember attack

This paper furthers the research of Rollo, Luther and Atkinson 1999, and Rollo, Honey, Atkinson and Luther 2003, regarding the way in which building shape appears to contribute to the collection of fire-brand debris subject to ember attack. The paper will present a range of 2D fluid-mapping and 3D wind tunnel studies (Melaragno 1982) which have been correlated with the transportation characteristics of an ember laden air-field (Cheney and Sullivan 1997). Working with a range of generic building types the paper also introduces simple spatial modelling techniques which are being developed to illustrate the relationship between ember capture and changes in wind speed and air pressure.

Novel spectral descriptor for object shape

In this paper, we propose a novel descriptor for shapes. The proposed descriptor is obtained from 3D spherical harmonics. The inadequacy of 2D spherical harmonics is addressed and the method to obtain 3D spherical harmonics is described. 3D spherical harmonics requires construction of a 3D model which implicitly represents rich features of objects. Spherical harmonics are used to obtain descriptors from the 3D models. The performance of the proposed method is compared against the CSS approach which is the MPEG-7 descriptor for shape contour. MPEG-7 dataset of shape contours, namely, CE-1 is used to perform the experiments. It is shown that the proposed method is effective.

Connectivity-based shape descriptors

In this paper, we propose a method for indexing and retrieval of images based on shapes of objects. The concept of connectivity is introduced. 3D models are used to represent 2D images. 2D images are decomposed a priori using connectivity which is followed by 3D model construction. 3D model descriptors are obtained for 3D models and used to represent the underlying 2D shapes. We have used spherical harmonics descriptors as the 3D model descriptors. Difference between two images is computed as the Euclidean distance between their descriptors. Experiments are performed to test the effectiveness of spherical harmonics for retrieval of 2D images. The proposed method is compared with methods based on principal components analysis (PCA) and generic Fourier descriptors (GFD). It is found that the proposed method is effective. Item S8 within the MPEG-7 still images content set is used for performing experiments.

Spectral shape descriptor using spherical harmonics

In this paper, we propose a spectral descriptor for shapes of objects. The method relies on transforming the 2D objects into 3D space; distance transform and scale space theory is used to transform objects into 3D space. Spherical harmonics of the voxel grid are used to obtain shape descriptors. The proposed methods are compared against two existing methods which use spherical harmonics for shape based retrieval of images. Comparison is done based on ranking of images which is articulated in recall-precision curves. MPEG-7 Still Images Content Set is used for performing experiments. Experimental results show that the performance of the proposed descriptor is significantly better than other methods in the same category.

Fusion based 3D tracking of mobile transmitters via robust set-valued state estimation with RSS measurements

This paper investigates the problem of location and velocity detection of a mobile agent using Received Signal Strength (RSS) measurements captured by geographically distributed seed nodes. With inherently nonlinear power measurements, we derive a powerful linear measurement scheme using an analytical measurement conversion technique which can readily be used with RSS measuring sensors. We also employ the concept of sensor fusion in conjunction for the case of redundant measurements to further enhance the estimation accuracy.

A systems approach to shape and topology optimisation of mechanical structures

Optimisation techniques have become more and more important as the possibility of simulating complex mechanical structures has become a reality. A common tool in the layout design of structural parts is the topology optimisation method, which finds an optimum material distribution within a given geometrical design space to best meet loading conditions and constraints. Another important method is shape optimisation, which optimises weight given parametric geometric constraints. In the case of complex shaped parts or elaborate assemblies, for example automobile body structures, shape optimisation is still hard to do; mainly due to the difficulty in translating shape design parameters into meaningful analysis models. Tools like the parametric geometry package SFE CONCEPT are designed to mitigate these issues. Nevertheless, shape methods usually cannot suggest new load path configurations, while topology methods are often confined to single parts. To overcome these limitations the authors have developed a method that combines both approaches into an Integral Shape/Topology Method (IST) that is capable of finding new optimal solutions. This is achieved by an automated optimisation loop and can be applied for both thin walled structures as well as solid 3D geometries. When optimising structures by applying IST, global optimum solutions can be determined that may not be obtained with isolated shape- or topology-optimisation methods.

Temperature variations at nano-scale level in phase transformed nanocrystalline NiTi shape memory alloys adjacent to graphene layers

The detection and control of the temperature variation at the nano-scale level of thermo-mechanical materials during a compression process have been challenging issues. In this paper, an empirical method is proposed to predict the temperature at the nano-scale level during the solid-state phase transition phenomenon in NiTi shape memory alloys. Isothermal data was used as a reference to determine the temperature change at different loading rates. The temperature of the phase transformed zone underneath the tip increased by _3 to 40 _C as the loading rate increased. The temperature approached a constant with further increase in indentation depth. A few layers of graphene were used to enhance the cooling process at different loading rates. Due to the presence of graphene layers the temperature beneath the tip decreased by a further _3 to 10 _C depending on the loading rate. Compared with highly polished NiTi, deeper indentation depths were also observed during the solidstate phase transition, especially at the rate dependent zones. Larger superelastic deformations confirmed that the latent heat transfer through the deposited graphene layers allowed a larger phase transition volume and, therefore, more stress relaxation and penetration depth.