Development of configural 3D object recognition

There is evidence for the late development in humans of configural face and animal recognition. We show that the recognition of artificial three-dimensional (3D) objects from part configurations develops similarly late. We also demonstrate that the cross-modal integration of object information reinforces the development of configural recognition more than the intra-modal integration does. Multimodal object representations in the brain may therefore play a role in configural object recognition. © 2003 Elsevier B.V. All rights reserved.

Arbitrary real-time three-dimensional corporal object sensing and reconstruction scheme

A real-time three-dimensional (3D) object sensing and reconstruction scheme is presented that can be applied on any arbitrary corporeal shape. Operation is demonstrated on several calibrated objects. The system uses curvature sensors based upon in-line fiber Bragg gratings encapsulated in a low-temperature curing synthetic silicone. New methods to quantitatively evaluate the performance of a 3D object-sensing scheme are developed and appraised. It is shown that the sensing scheme yields a volumetric error of 1% to 9%, depending on the object.

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

Automatic object segmentation from calibrated images

This paper addresses the problem of automatically obtaining the object/background segmentation of a rigid 3D object observed in a set of images that have been calibrated for camera pose and intrinsics. Such segmentations can be used to obtain a shape representation of a potentially texture-less object by computing a visual hull. We propose an automatic approach where the object to be segmented is identified by the pose of the cameras instead of user input such as 2D bounding rectangles or brush-strokes. The key behind our method is a pairwise MRF framework that combines (a) foreground/background appearance models, (b) epipolar constraints and (c) weak stereo correspondence into a single segmentation cost function that can be efficiently solved by Graph-cuts. The segmentation thus obtained is further improved using silhouette coherency and then used to update the foreground/background appearance models which are fed into the next Graph-cut computation. These two steps are iterated until segmentation convergences. Our method can automatically provide a 3D surface representation even in texture-less scenes where MVS methods might fail. Furthermore, it confers improved performance in images where the object is not readily separable from the background in colour space, an area that previous segmentation approaches have found challenging. © 2011 IEEE.

A flexible, extensible object oriented real-time near photorealistic visualization system:the system framework design

In this paper we describe a novel, extensible visualization system currently under development at Aston University. We introduce modern programming methods, such as the use of data driven programming, design patterns, and the careful definition of interfaces to allow easy extension using plug-ins, to 3D landscape visualization software. We combine this with modern developments in computer graphics, such as vertex and fragment shaders, to create an extremely flexible, extensible real-time near photorealistic visualization system. In this paper we show the design of the system and the main sub-components. We stress the role of modern programming practices and illustrate the benefits these bring to 3D visualization. © 2006 Springer-Verlag Berlin Heidelberg.

The detection and identification of extraneous metals in material conveyance systems

The aim of this work was to design and build an equipment which can detect ferrous and non-ferrous objects in conveyed commodities, discriminate between them and locate the object along the belt and on the width of the belt. The magnetic induction mechanism was used as a means of achieving the objectives of this research. In order to choose the appropriate geometry and size of the induction field source, the field distributions of different source geometries and sizes were studied in detail. From these investigations it was found the square loop geometry is the most appropriate as a field generating source for the purpose of this project. The phenomena of field distribution in the conductors was also investigated. An equipment was designed and built at the preliminary stages of thework based on a flux-gate magnetometer with the ability to detect only ferrous objects.The instrument was designed such that it could be used to detect ferrous objects in the coal conveyors of power stations. The advantages of employing this detector in the power industry over the present ferrous metal electromagnetic separators were also considered. The objectives of this project culminated in the design and construction of a ferrous and non-ferrous detector with the ability to discriminate between ferrous and non-ferrous metals and to locate the objects on the conveying system. An experimental study was carried out to test the performance of the equipment in the detection of ferrous and non-ferrous objects of a given size carried on the conveyor belt. The ability of the equipment to discriminate between the types of metals and to locate the object on the belt was also evaluated experimentally. The benefits which can be gained from the industrial implementations of the equipment were considered. Further topics which may be investigated as an extension of this work are given.

Retinal drusen detection using the Nidek F-10 SLO in retro-mode

Presentaton Purpose:We conducted a small study to assess the novel, retro - mode imaging technique of the NIDEK F-10 scanning laser ophthalmoscope, for detecting and quantifying retinal drusen. Methods:Fundus photographs of 4 eyes of 2 patients taken in retro-mode on the Nidek F-10 SLO were graded independently by 6,experienced, masked fundus graders for the presence of retinal drusen , and compared to stereo colour fundus photographs taken with a Topcon TRC-50DX camera. Results:The mean number of retinal drusen detected in retro mode was 142.96+/- 60.8, range 63-265, and on colour fundus photography mean of 66.6+/-32.6, range 26-177. All observers independently detected approximately twice as many drusen on retro-mode than colour fundus photography (p<0.0001, Student’s paired t-test) . The statistical significance of interobserver variation in drusen detection was p=0.07 on colour fundus photography , and p=0.02 on retro mode ( ANOVA) . Conclusions:The retro-mode of the F-10 camera uses infrared laser and an aperture with a modified central stop, with the aperture deviated laterally from the confocal light path. This forms a pseudo -3D image which is a new means of detecting abnomalites in the deeper retinal layers. Retro-mode imaging of retinal drusen using the F-10 Nidek SLO is a highly sensitive technique for detecting and quantifying retinal drusen , and detected twice as many drusen than colour fundus photography. This small pilot study suggests that this novel type of imaging may have a role in the future detection and analysis of retinal drusen, a field that is likely to become increasingly important in future AMD prevention studies.

Real-time 3D shape sensing and reconstruction scheme based upon fibre optic bragg gratings

An array of FBG curvature sensors are wavelength-interrogated and the recovered data combined with a three-dimensional algorithm to reconstruct in real time the enveloped object with a 1% to 9% volumetric error. © 2012 OSA.

Late development of metric part-relational processing in object recognition

Four experiments with unfamiliar objects examined the remarkably late consolidation of part-relational relative to part-based object recognition (Jüttner, Wakui, Petters, Kaur, & Davidoff, 2013). Our results indicate a particularly protracted developmental trajectory for the processing of metric part relations. Schoolchildren aged 7 to 14 years and adults were tested in 3-Alternative-Forced-Choice tasks to judge the correct appearance of upright and inverted newly learned multipart objects that had been manipulated in terms of individual parts or part relations. Experiment 1 showed that even the youngest tested children were close to adult levels of performance for recognizing categorical changes of individual parts and relative part position. By contrast, Experiment 2 demonstrated that performance for detecting metric changes of relative part position was distinctly reduced in young children compared with recognizing metric changes of individual parts, and did not approach the latter until 11 to 12 years. A similar developmental dissociation was observed in Experiment 3, which contrasted the detection of metric relative-size changes and metric part changes. Experiment 4 showed that manipulations of metric size that were perceived as part (rather than part-relational) changes eliminated this dissociation. Implications for theories of object recognition and similarities to the development of face perception are discussed. © 2014 American Psychological Association.

A stable graph-based representation for object recognition through high-order matching

Many Object recognition techniques perform some flavour of point pattern matching between a model and a scene. Such points are usually selected through a feature detection algorithm that is robust to a class of image transformations and a suitable descriptor is computed over them in order to get a reliable matching. Moreover, some approaches take an additional step by casting the correspondence problem into a matching between graphs defined over feature points. The motivation is that the relational model would add more discriminative power, however the overall effectiveness strongly depends on the ability to build a graph that is stable with respect to both changes in the object appearance and spatial distribution of interest points. In fact, widely used graph-based representations, have shown to suffer some limitations, especially with respect to changes in the Euclidean organization of the feature points. In this paper we introduce a technique to build relational structures over corner points that does not depend on the spatial distribution of the features. © 2012 ICPR Org Committee.

Practical 3D reconstruction based on photometric stereo

Photometric Stereo is a powerful image based 3D reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3D scene under multiple different illuminations. As a result the 3D scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3D surfaces. The aim of this Chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3D acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3D reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the Chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results. © 2010 Springer-Verlag Berlin Heidelberg.