Gait Dynamics for Recognition and Classification

This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features.

How do Humans Determine Reflectance Properties under Unknown Illumination?

Under normal viewing conditions, humans find it easy to distinguish between objects made out of different materials such as plastic, metal, or paper. Untextured materials such as these have different surface reflectance properties, including lightness and gloss. With single isolated images and unknown illumination conditions, the task of estimating surface reflectance is highly underconstrained, because many combinations of reflection and illumination are consistent with a given image. In order to work out how humans estimate surface reflectance properties, we asked subjects to match the appearance of isolated spheres taken out of their original contexts. We found that subjects were able to perform the task accurately and reliably without contextual information to specify the illumination. The spheres were rendered under a variety of artificial illuminations, such as a single point light source, and a number of photographically-captured real-world illuminations from both indoor and outdoor scenes. Subjects performed more accurately for stimuli viewed under real-world patterns of illumination than under artificial illuminations, suggesting that subjects use stored assumptions about the regularities of real-world illuminations to solve the ill-posed problem.

Light Field Morphable Models

Statistical shape and texture appearance models are powerful image representations, but previously had been restricted to 2D or simple 3D shapes. In this paper we present a novel 3D morphable model based on image-based rendering techniques, which can represent complex lighting conditions, structures, and surfaces. We describe how to construct a manifold of the multi-view appearance of an object class using light fields and show how to match a 2D image of an object to a point on this manifold. In turn we use the reconstructed light field to render novel views of the object. Our technique overcomes the limitations of polygon based appearance models and uses light fields that are acquired in real-time.

Learning and Example Selection for Object and Pattern Detection

This thesis presents a learning based approach for detecting classes of objects and patterns with variable image appearance but highly predictable image boundaries. It consists of two parts. In part one, we introduce our object and pattern detection approach using a concrete human face detection example. The approach first builds a distribution-based model of the target pattern class in an appropriate feature space to describe the target's variable image appearance. It then learns from examples a similarity measure for matching new patterns against the distribution-based target model. The approach makes few assumptions about the target pattern class and should therefore be fairly general, as long as the target class has predictable image boundaries. Because our object and pattern detection approach is very much learning-based, how well a system eventually performs depends heavily on the quality of training examples it receives. The second part of this thesis looks at how one can select high quality examples for function approximation learning tasks. We propose an {em active learning} formulation for function approximation, and show for three specific approximation function classes, that the active example selection strategy learns its target with fewer data samples than random sampling. We then simplify the original active learning formulation, and show how it leads to a tractable example selection paradigm, suitable for use in many object and pattern detection problems.

Imaging of three-dimensional objects in emission electron microscopy

Under investigation by emission electron microscopy, the shape and size of three-dimensional objects are distorted because of the appearance of a characteristic potential relief and a possible contact potential difference between the particles and the substrate. An estimation of these effects for spherical particles is made. It is shown that the apparent size of particles observed in an emission electron microscope (EEM) could be increased as well as decreased depending on the relation between the work functions of the particle and the substrate. The corresponding formulae are given and several possibilities are shown which permit us to determine from the EEM image the real size of particles and their work function relative to the substrate.

Computer Recognition of Prismatic Solids

An investigation is made into the problem of constructing a model of the appearance to an optical input device of scenes consisting of plane-faced geometric solids. The goal is to study algorithms which find the real straight edges in the scenes, taking into account smooth variations in intensity over faces of the solids, blurring of edges and noise. A general mathematical analysis is made of optimal methods for identifying the edge lines in figures, given a raster of intensities covering the entire field of view. There is given in addition a suboptimal statistical decision procedure, based on the model, for the identification of a line within a narrow band on the field of view given an array of intensities from within the band. A computer program has been written and extensively tested which implements this procedure and extracts lines from real scenes. Other programs were written which judge the completeness of extracted sets of lines, and propose and test for additional lines which had escaped initial detection. The performance of these programs is discussed in relation to the theory derived from the model, and with regard to their use of global information in detecting and proposing lines.

TEMPEST: A Template Editor for Structured Text

TEMPEST is a full-screen text editor that incorporates a structural paradigm in addition to the more traditional textual paradigm provided by most editors. While the textual paradigm treats the text as a sequence of characters, the structural paradigm treats it as a collection of named blocks which the user can define, group, and manipulate. Blocks can be defined to correspond to the structural features of he text, thereby providing more meaningful objects to operate on than characters of lines. The structural representation of the text is kept in the background, giving TEMPEST the appearance of a typical text editor. The structural and textual interfaces coexist equally, however, so one can always operate on the text from wither point of view. TEMPEST's representation scheme provides no semantic understanding of structure. This approach sacrifices depth, but affords a broad range of applicability and requires very little computational overhead. A prototype has been implemented to illustrate the feasibility and potential areas of application of the central ideas. It was developed and runs on an IBM Personal Computer.

McArdle disease: a unique study model in sports medicine

McArdle disease is arguably the paradigm of exercise intolerance in humans. This disorder is caused by inherited deficiency of myophosphorylase, the enzyme isoform that initiates glycogen breakdown in skeletal muscles. Because patients are unable to obtain energy from their muscle glycogen stores, this disease provides an interesting model of study for exercise physiologists, allowing insight to be gained into the understanding of glycogen-dependent muscle functions. Of special interest in the field of muscle physiology and sports medicine are also some specific (if not unique) characteristics of this disorder, such as the so-called 'second wind' phenomenon, the frequent exercise-induced rhabdomyolysis and myoglobinuria episodes suffered by patients (with muscle damage also occurring under basal conditions), or the early appearance of fatigue and contractures, among others. In this article we review the main pathophysiological features of this disorder leading to exercise intolerance as well as the currently available therapeutic possibilities.

Accurate Range Image Registration: Eliminating or Modelling Outliers

Liu, Yonghuai, Liu, Honghai, Li, Longzhuang, Wei, Baogang. Accurate Range Image Registration: Eliminating or Modelling Outliers. Proceedings of 12th IEEE Conference on Emerging Technologies and Factory Automation, 2007, pp. 1316-1323. Sponsorship: IEEE

Automatic 3d free form shape matching using the graduated assignment algorithm.

Liu, Yonghuai. Automatic 3d free form shape matching using the graduated assignment algorithm. Pattern Recognition, vol. 38, no. 10, pp. 1615-1631, 2005.

Model-based detection of spiculated lesions in mammograms

R. Zwiggelaar, T.C. Parr, J.E. Schumm. I.W. Hutt, S.M. Astley, C.J. Taylor and C.R.M. Boggis, 'Model-based detection of spiculated lesions in mammograms', Medical Image Analysis 3 (1), 39-62 (1999)

Children drawing toy commercials: re-imagining television production features

Griffiths, M. (2005). Children drawing toy commercials: re-imagining television production features. Visual Communication. 4(1), pp.21-37. RAE2008

The impact of short duration, high intensity exercise on cardiac troponin release

The aim of this study was to assess the appearance of cardiac troponins (cTnI and/or cTnT) after a short bout (30 s) of ‘all-out’ intense exercise and to determine the stability of any exercise-related cTnI release in response to repeated bouts of high intensity exercise separated by 7 days recovery. Eighteen apparently healthy, physically active, male university students completed two all-out 30 s cycle sprint, separated by 7 days. cTnI, blood lactate and catecholamine concentrations were measured before, immediately after and 24 h after each bout. Cycle performance, heart rate and blood pressure responses to exercise were also recorded. Cycle performance was modestly elevated in the second trial [6·5% increase in peak power output (PPO)]; there was no difference in the cardiovascular, lactate or catecholamine response to the two cycle trials. cTnI was not significantly elevated from baseline through recovery (Trial 1: 0·06 ± 0·04 ng ml−1, 0·05 ± 0·04 ng ml−1, 0·03 ± 0·02 ng ml−1; Trial 2: 0·02 ± 0·04 ng ml−1, 0·04 ± 0·03 ng ml−1, 0·05 ± 0·06 ng ml−1) in either trial. Very small within subject changes were not significantly correlated between the two trials (r = 0·06; P>0·05). Subsequently, short duration, high intensity exercise does not elicit a clinically relevant response in cTnI and any small alterations likely reflect the underlying biological variability of cTnI measurement within the participants.

(O)znaki śmierci w polskiej poezji po roku 1956

Wydział Filologii Polskiej i Klasycznej: Instytut Filologii Polskiej