How are Three-Deminsional Objects Represented in the Brain?

We discuss a variety of object recognition experiments in which human subjects were presented with realistically rendered images of computer-generated three-dimensional objects, with tight control over stimulus shape, surface properties, illumination, and viewpoint, as well as subjects' prior exposure to the stimulus objects. In all experiments recognition performance was: (1) consistently viewpoint dependent; (2) only partially aided by binocular stereo and other depth information, (3) specific to viewpoints that were familiar; (4) systematically disrupted by rotation in depth more than by deforming the two-dimensional images of the stimuli. These results are consistent with recently advanced computational theories of recognition based on view interpolation

Unfamiliar facial identity registration and recognition performance enhancement

The work in this thesis aims at studying the problems related to the robustness of a face recognition system where specific attention is given to the issues of handling the image variation complexity and inherent limited Unique Characteristic Information (UCI) within the scope of unfamiliar identity recognition environment. These issues will be the main themes in developing a mutual understanding of extraction and classification tasking strategies and are carried out as a two interdependent but related blocks of research work. Naturally, the complexity of the image variation problem is built up from factors including the viewing geometry, illumination, occlusion and other kind of intrinsic and extrinsic image variation. Ideally, the recognition performance will be increased whenever the variation is reduced and/or the UCI is increased. However, the variation reduction on 2D facial images may result in loss of important clues or UCI data for a particular face alternatively increasing the UCI may also increase the image variation. To reduce the lost of information, while reducing or compensating the variation complexity, a hybrid technique is proposed in this thesis. The technique is derived from three conventional approaches for the variation compensation and feature extraction tasks. In this first research block, transformation, modelling and compensation approaches are combined to deal with the variation complexity. The ultimate aim of this combination is to represent (transformation) the UCI without losing the important features by modelling and discard (compensation) and reduce the level of the variation complexity of a given face image. Experimental results have shown that discarding a certain obvious variation will enhance the desired information rather than sceptical in losing the interested UCI. The modelling and compensation stages will benefit both variation reduction and UCI enhancement. Colour, gray level and edge image information are used to manipulate the UCI which involve the analysis on the skin colour, facial texture and features measurement respectively. The Derivative Linear Binary transformation (DLBT) technique is proposed for the features measurement consistency. Prior knowledge of input image with symmetrical properties, the informative region and consistency of some features will be fully utilized in preserving the UCI feature information. As a result, the similarity and dissimilarity representation for identity parameters or classes are obtained from the selected UCI representation which involves the derivative features size and distance measurement, facial texture and skin colour. These are mainly used to accommodate the strategy of unfamiliar identity classification in the second block of the research work. Since all faces share similar structure, classification technique should be able to increase the similarities within the class while increase the dissimilarity between the classes. Furthermore, a smaller class will result on less burden on the identification or recognition processes. The proposed method or collateral classification strategy of identity representation introduced in this thesis is by manipulating the availability of the collateral UCI for classifying the identity parameters of regional appearance, gender and age classes. In this regard, the registration of collateral UCI s have been made in such a way to collect more identity information. As a result, the performance of unfamiliar identity recognition positively is upgraded with respect to the special UCI for the class recognition and possibly with the small size of the class. The experiment was done using data from our developed database and open database comprising three different regional appearances, two different age groups and two different genders and is incorporated with pose and illumination image variations

Viewer-Centered Object Recognition in Monkeys

How does the brain recognize three-dimensional objects? We trained monkeys to recognize computer rendered objects presented from an arbitrarily chosen training view, and subsequently tested their ability to generalize recognition for other views. Our results provide additional evidence in favor of with a recognition model that accomplishes view-invariant performance by storing a limited number of object views or templates together with the capacity to interpolate between the templates (Poggio and Edelman, 1990)

Perceiving Illumination Inconsistencies in Scenes

The human visual system is adept at detecting and encoding statistical regularities in its spatio-temporal environment. Here we report an unexpected failure of this ability in the context of perceiving inconsistencies in illumination distributions across a scene. Contrary to predictions from previous studies [Enns and Rensink, 1990; Sun and Perona, 1996a, 1996b, 1997], we find that the visual system displays a remarkable lack of sensitivity to illumination inconsistencies, both in experimental stimuli and in images of real scenes. Our results allow us to draw inferences regarding how the visual system encodes illumination distributions across scenes. Specifically, they suggest that the visual system does not verify the global consistency of locally derived estimates of illumination direction

3D Reconstruction using Active Illumination

In this thesis we present a pipeline for 3D model acquisition. Generating 3D models of real-world objects is an important task in computer vision with many applications, such as in 3D design, archaeology, entertainment, and virtual or augmented reality. The contribution of this thesis is threefold: we propose a calibration procedure for the cameras, we describe an approach for capturing and processing photometric normals using gradient illuminations in the hardware set-up, and finally we present a multi-view photometric stereo 3D reconstruction method. In order to obtain accurate results using multi-view and photometric stereo reconstruction, the cameras are calibrated geometrically and photometrically. For acquiring data, a light stage is used. This is a hardware set-up that allows to control the illumination during acquisition. The procedure used to generate appropriate illuminations and to process the acquired data to obtain accurate photometric normals is described. The core of the pipeline is a multi-view photometric stereo reconstruction method. In this method, we first generate a sparse reconstruction using the acquired images and computed normals. In the second step, the information from the normal maps is used to obtain a dense reconstruction of an object’s surface. Finally, the reconstructed surface is filtered to remove artifacts introduced by the dense reconstruction step

Stereoscopic Sketchpad: 3D Digital Ink

--Context-- This project looked at the development of a stereoscopic 3D environment in which a user is able to draw freely in all three dimensions. The main focus was on the storage and manipulation of the ‘digital ink’ with which the user draws. For a drawing and sketching package to be effective it must not only have an easy to use user interface, it must be able to handle all input data quickly and efficiently so that the user is able to focus fully on their drawing. --Background-- When it comes to sketching in three dimensions the majority of applications currently available rely on vector based drawing methods. This is primarily because the applications are designed to take a users two dimensional input and transform this into a three dimensional model. Having the sketch represented as vectors makes it simpler for the program to act upon its geometry and thus convert it to a model. There are a number of methods to achieve this aim including Gesture Based Modelling, Reconstruction and Blobby Inflation. Other vector based applications focus on the creation of curves allowing the user to draw within or on existing 3D models. They also allow the user to create wire frame type models. These stroke based applications bring the user closer to traditional sketching rather than the more structured modelling methods detailed. While at present the field is inundated with vector based applications mainly focused upon sketch-based modelling there are significantly less voxel based applications. The majority of these applications focus on the deformation and sculpting of voxmaps, almost the opposite of drawing and sketching, and the creation of three dimensional voxmaps from standard two dimensional pixmaps. How to actually sketch freely within a scene represented by a voxmap has rarely been explored. This comes as a surprise when so many of the standard 2D drawing programs in use today are pixel based. --Method-- As part of this project a simple three dimensional drawing program was designed and implemented using C and C++. This tool is known as Sketch3D and was created using a Model View Controller (MVC) architecture. Due to the modular nature of Sketch3Ds system architecture it is possible to plug a range of different data structures into the program to represent the ink in a variety of ways. A series of data structures have been implemented and were tested for efficiency. These structures were a simple list, a 3D array, and an octree. They have been tested for: the time it takes to insert or remove points from the structure; how easy it is to manipulate points once they are stored; and also how the number of points stored effects the draw and rendering times. One of the key issues brought up by this project was devising a means by which a user is able to draw in three dimensions while using only two dimensional input devices. The method settled upon and implemented involves using the mouse or a digital pen to sketch as one would in a standard 2D drawing package but also linking the up and down keyboard keys to the current depth. This allows the user to move in and out of the scene as they draw. A couple of user interface tools were also developed to assist the user. A 3D cursor was implemented and also a toggle, which when on, highlights all of the points intersecting the depth plane on which the cursor currently resides. These tools allow the user to see exactly where they are drawing in relation to previously drawn lines. --Results-- The tests conducted on the data structures clearly revealed that the octree was the most effective data structure. While not the most efficient in every area, it manages to avoid the major pitfalls of the other structures. The list was extremely quick to render and draw to the screen but suffered severely when it comes to finding and manipulating points already stored. In contrast the three dimensional array was able to erase or manipulate points effectively while the draw time rendered the structure effectively useless, taking huge amounts of time to draw each frame. The focus of this research was on how a 3D sketching package would go about storing and accessing the digital ink. This is just a basis for further research in this area and many issues touched upon in this paper will require a more in depth analysis. The primary area of this future research would be the creation of an effective user interface and the introduction of regular sketching package features such as the saving and loading of images