Algorithms for multi-modal human movement and behaviour monitoring

This thesis describes investigations into improvements in the field of automated people tracking using multi-modal infrared (IR) and visible image information. The research question posed is; “To what extent can infrared image information be used to improve visible light based human tracking systems?” Automated passive tracking of human subjects is an active research area which has been approached in many ways. Typical approaches include the segmentation of the foreground, the location of humans, model initialisation and subject tracking. Sensor reliability evaluation and fusion methods are also key research areas in multi-modal systems. Shifting illumination and shadows can cause issues with visible images when attempting to extract foreground regions. Images from thermal IR cameras, which use long-wavelength infrared (LWIR) sensors, demonstrate high invariance to illumination. It is shown that thermal IR images often provide superior foreground masks using pixel level statistical extraction techniques in many scenarios. Experiments are performed to determine if cues are present at the data level that may indicate the quality of the sensor as an input. Modality specific measures are proposed as possible indicators of sensor quality (determined by foreground extraction capability). A sensor and application specific method for scene evaluation is proposed, whereby sensor quality is measured at the pixel level. A neuro-fuzzy inference system is trained using the scene quality measures to assess a series of scenes and make a modality decision

Piecewise Affine Registration of Biological Images for Volume Reconstruction

This manuscript tackles the reconstruction of 3D volumes via mono-modal registration of series of 2D biological images (histological sections, autoradiographs, cryosections, etc.). The process of acquiring these images typically induces composite transformations that we model as a number of rigid or affine local transformations embedded in an elastic one. We propose a registration approach closely derived from this model. Given a pair of input images, we first compute a dense similarity field between them with a block matching algorithm. We use as a similarity measure an extension of the classical correlation coefficient that improves the consistency of the field. A hierarchical clustering algorithm then automatically partitions the field into a number of classes from which we extract independent pairs of sub-images. Our clustering algorithm relies on the Earth mover’s distribution metric and is additionally guided by robust least-square estimation of the transformations associated with each cluster. Finally, the pairs of sub-images are, independently, affinely registered and a hybrid affine/non-linear interpolation scheme is used to compose the output registered image. We investigate the behavior of our approach on several batches of histological data and discuss its sensitivity to parameters and noise

Similarity score of two images using different measures.

In the field of computer vision and image processing, image similarity has been a central concern for decades. If you compare two pictures, Image Similarity returns a value that tells you how physically they are close. A quantitative measure of the degree of correspondence between the images concerned is given by this test. The score of the similarity between images varies from 0 to 1. In this paper, ORB (Oriented Fast Rotated Brief) algorithm is used to measure the similarity and other types of similarity measures like Structural Similarity Index (SSIM), pixel similarity, Earth mover's Distance are used to obtain the score. When two images are compared, it shows how much identical (common) objects are there in the two images. So, the accuracy or similarity score is about 87 percent when the two images are compared

Development of cortical shape in the human brain from 6 to 24months of age via a novel measure of shape complexity

The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental disorders. We propose a novel cortical shape measure, referred to as the ‘shape complexity index’ (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6 months of age and were reduced at 24 months, with the difference pattern switching from higher complexity in males at 6 months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24 months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development

Directional Ringlet Intensity Feature Transform for Tracking

The challenges existing for current intensity-based histogram feature tracking methods in wide area motion imagery include object structural information distortions and background variations, such as different pavement or ground types. All of these challenges need to be met in order to have a robust object tracker, while attaining to be computed at an appropriate speed for real-time processing. To achieve this we propose a novel method, Directional Ringlet Intensity Feature Transform (DRIFT), that employs Kirsch kernel filtering and Gaussian ringlet feature mapping. We evaluated the DRIFT on two challenging datasets, namely Columbus Large Image Format (CLIF) and Large Area Image Recorder (LAIR), to evaluate its robustness and efficiency. Experimental results show that the proposed approach yields the highest accuracy compared to state-of-the-art object tracking methods

On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis

Background: Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. Methods: The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object’s centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. Results: After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field – were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. Conclusions: The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction

Mapping of multiple muscles with transcranial magnetic stimulation: Absolute and relative test-retest reliability

The spatial accuracy of transcranial magnetic stimulation (TMS) may be as small as a few millimeters. Despite such great potential, navigated TMS (nTMS) mapping is still underused for the assessment of motor plasticity, particularly in clinical settings. Here, we investigate the within‐limb somatotopy gradient as well as absolute and relative reliability of three hand muscle cortical representations (MCRs) using a comprehensive grid‐based sulcus‐informed nTMS motor mapping. We enrolled 22 young healthy male volunteers. Two nTMS mapping sessions were separated by 5–10 days. Motor evoked potentials were obtained from abductor pollicis brevis (APB), abductor digiti minimi, and extensor digitorum communis. In addition to individual MRI‐based analysis, we studied normalized MNI MCRs. For the reliability assessment, we calculated intraclass correlation and the smallest detectable change. Our results revealed a somatotopy gradient reflected by APB MCR having the most lateral location. Reliability analysis showed that the commonly used metrics of MCRs, such as areas, volumes, centers of gravity (COGs), and hotspots had a high relative and low absolute reliability for all three muscles. For within‐limb TMS somatotopy, the most common metrics such as the shifts between MCR COGs and hotspots had poor relative reliability. However, overlaps between different muscle MCRs were highly reliable. We, thus, provide novel evidence that inter‐muscle MCR interaction can be reliably traced using MCR overlaps while shifts between the COGs and hotspots of different MCRs are not suitable for this purpose. Our results have implications for the interpretation of nTMS motor mapping results in healthy subjects and patients with neurological conditions

DIGITAL IMAGE PROCESSING FOR ULTRASONIC THERAPY AND TENDINOUS INJURY

In this master\u27s thesis, several digital image processing techniques are explored for potential in evaluation of Brightness mode (B-mode) ultrasound images. Currently, many processing techniques are utilized during ultrasound visualization in cardiovascular applications, mammography, and three-dimensional ultrasound systems. However, approaches that serve to aid the clinician in diagnostic assessment of tendinous and ligamentous injuries are more limited. Consequently, the methods employed below are aimed at reducing the dependence on clinician judgment alone to assess the healing stage and mechanical properties of tendinous injuries. Initial focus concentrated on the use of entropy in texture analysis to relate a tendon\u27s appearance in an ultrasound image to its mechanical integrity. Confounding effects such as motion artifacts and region of interest selection by the user limited the applicability of small regions selected for analysis, but general trends were observed when the entire visualized tendon or superficial background region was selected. Entropy calculations suggested a significant change in texture pattern for tendinous regions compared to the selected background regions. In order to reduce the impact of motion artifacts and dependence of the texture analysis on manual identification of regions of interest, a Matlab® script was developed intended to isolate the tendinous regions of interest for further analysis. Methods for segmentation employed relied on a moving window Fourier Transform to compare local parameters in the image to a predefined window of tendinous tissue. Further assessment of each local region benefited from parameterization of the local window\u27s properties that focused on capturing indicators of mean pixel intensity, local variation in pixel intensity, and local directionality consistency derived from the spatial frequency patterns observed in the Fourier Transforms via comparison by the circular Earth Mover\u27s Distance. Results of the segmentation algorithm developed indicated the presence of directional consistency within the tendinous regions, and changes in the speckle pattern were observed for the image derived from mean intensity and local pixel intensity variation. However, non-tendinous regions were also identified for their directional consistency, limiting the applicability of the current process in tendinous region isolation. The results obtained for calculations of the circular Earth Mover\u27s Distance improved slightly with the inclusion of temporal averaging and image registration, but still require improvement before implementation in clinical applications can be realized

A generalisable framework for saliency-based line segment detection

Here we present a novel, information-theoretic salient line segment detector. Existing line detectors typically only use the image gradient to search for potential lines. Consequently, many lines are found, particularly in repetitive scenes. In contrast, our approach detects lines that define regions of significant divergence between pixel intensity or colour statistics. This results in a novel detector that naturally avoids the repetitive parts of a scene while detecting the strong, discriminative lines present. We furthermore use our approach as a saliency filter on existing line detectors to more efficiently detect salient line segments. The approach is highly generalisable, depending only on image statistics rather than image gradient; and this is demonstrated by an extension to depth imagery. Our work is evaluated against a number of other line detectors and a quantitative evaluation demonstrates a significant improvement over existing line detectors for a range of image transformation

Shared Habitats: the MoverWitness Paradigm

Merged with duplicate record 10026.1/642 on 14.02.2017 by CS (TIS)This practice-led research thesis analyses and visualises central components of Authentic Movement, with particular reference to the work of Dr Janet Adler. By contextualising and comparing this improvisation method with modern, post-modern and contemporary movement practices the author describes the emergence of Authentic Movement and distinguishes it from other practices. A new and original viewpoint is adopted and the practice's aesthetic, visual and empathetic characteristics are explored in relationship to and through visual art. The author, a learned Authentic Movement practitioner, critiques, deconstructs and reframes the practice from a visual arts- and performance-based, phenomenological perspective renaming it 'the MoverWitness exchange'. Embedded aspects and skills of the MoverWitness exchange, usually only accessible to firsthand practitioners of the method, are made explicit through research processes of analysis, application and visualisation. Hereby the practice's unique capacity to contain and express binary embodied experiences and concepts is exposed. Resulting insights are crystallised in a distinctive understanding of the MoverWitness exchange that emphasises its suitability as a new learning and/or research methodology for inter- and cross-disciplinary application.Dartington College of Art