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Needlework has been practiced throughout history, across the nation of Sweden and the world, primarily by women within the home. In recent years a revival of the craft has been seen worldwide, the covid lockdown and an aging population being two factors contributing to this. Historically there’s been a duality to the practice of needlework. On one hand, it’s been a means of oppression, and on the other hand, it's been a weapon of resistance and a source of joy, creativity, and collectivity. It has, throughout history, proven to be a political, social and creative tool and, as argued in this thesis, a spatial tool. The practice of needlework allows for the artisan to travel between different spheres. This thesis sets out to explore the potential of moving between private and public, performing a public domesticity through, for example, knitting.  Needlework is, in its nature, slow. This slowness, the repetitive movements of the hands and the touching of tactile materials emphasizes the process of making and prompts reflections and emotions. This thesis argues that methods of needlework as, for example, layering, mending, joining, ripping, and patching, clearly connect to the architectural design process. These methods emphasize notions of care and maintenance. The thesis uses an interdisciplinary approach to investigate needlework as both the topic of research and the means of spatial exploration and representation, aiming to underpin the relevance of engaging with needlework in the architectural design process, as a way of maintaining the craft and learning new things. Rooms devoted to the practice of needlework haven't appeared in a building plan for many years. The design proposal, presented in the report, aims to explore the possibility of these spaces reappearing within the public sphere. The proposal is placed within the context of Sweden with no specific site intended. Proposing a space of appearance (term coined by Hannah Arendt in her theory of Plurality) actualized through the collective making of the syjunta (sewing circle). Creating a public syrum (sewing room)  where the practice of needlework and its practitioners can appear, connected to ideas of feminist architectural practice to make the everyday visible. The thesis project engages with needlework by seeing it as a collective act of taking and making space.

Computer Aided Design (CAD) models often need to be processed due to data translation issues and requirements of the downstream applications like computational field simulation, rapid rototyping, computer graphics,computational manufacturing, and real-time rendering before they can be used. Automatic CAD model processing tools can significantly reduce the amount of time and cost associated with the manual processing.In this dissertaion, automated topology generation and feature removal techniques are developed to prepare suitable models with mimunum user interaction. A topology generation algorithm, commonly known as CAD repairing/healing, is presented to detect commonly found geometrical and topological issues like cracks, gaps, overlaps, intersections, T-connections, and no/invalid topology in the model, process them and build correct topological information. The present algorithm is based on the iterative vertex pair contraction and expansion operations called stitching and filling respectively. The algorithm closes small gaps/overlaps via the stitching operation and fills larger gaps by adding faces through the filling operation to process the model accurately. Processed models are guaranteed to be free of intersecting faces or surfaces. Moreover, the topology generation algorithm can process manifold as well as non-manifold models, which makes the procedure more general and flexible. This algorithm uses an automatic and adaptive distance threshold that enhances reliability of the process and preserves small features in the model. In addition, a spatial data structure, the octree, is used for searching and neighbor finding to process large models efficiently. In this way, the combination of generality, accuracy, reliability, and efficiency of this algorithm seems to be a significant improvement over existing techniques. Results are presented showing the effectiveness of the algorithm to process two- and three-dimensional configurations. Feature detection and removal and feature collapse algorithms are presented to detect and remove small features from CAD models automatically. The feature detection and removal algorithm uses a feature size measure based on the surface area and perimeter to detect small features accurately and remove them from the model. Small feature removal may create holes in the model that are post-processed using the stitching and/or filling operations of the topology generation algorithm. The feature collapse algorithm is based on the iterative vertex pair contraction operation, which is a generalization of an edge-collapse operation, to collapse small features. Unlike previous efforts that use edge-collapse as a dimension reduction operator, the feature collapse algorithm can pair up any arbitrary vertices and perform iterative vertex pair contraction to collapse small features as well as glue unconnected regions. Results showing the automatic detection and removal of most commonly found small features like small edges/faces, fillets, chamfers, nuts, and bolts from real mechanical parts are presented.

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<p>This thesis presents a computational model of the surgical stitching tasks and a path planning algorithm for robotic assisted stitching. The overall goal of the research is to enable surgical robots to perform automatic suturing. Suturing comprises several distinct steps, one of them is the stitching. During stitching, reaching the desired exit point is difficult because it must be accomplished without direct visual feedback. Moreover, the stitching is a time consuming procedure repeated multiple times during suturing. Therefore, it would be desirable to enhance the surgical robots with the ability of performing automatic suturing. The focus of this work is on the automation of the stitching task. The thesis presents a model based path planning algorithm for the autonomous stitching. The method uses a nonlinear model for the curved needle - soft tissue interaction. The tissue is modeled as a deformable object using continuum mechanics tools. This thesis uses a mesh free deformable tissue model namely, Reproducing Kernel Particle Method (RKPM). RKPM was chosen as it has been proven to accurately handle large deformation and requires no re-meshing algorithms. This method has the potential to be more realistic in modeling various material characteristics by using appropriate strain energy functions. The stitching task is simulated using a constrained deformable model; the deformable tissue is constrained by the interaction with the curved needle. The stitching model was used for needle trajectory path planning during stitching. This new path planning algorithm for the robotic stitching was developed, implemented, and evaluated. Several simulations and experiments were conducted. The first group of simulations comprised random insertions from different insertion points without planning to assess the modeling method and the trajectory of the needle inside the tissue. Then the parameters of the simulations were set according to the measured experimental parameters. The proposed path planning method was tested using a surgical ETHICON needle of type SH 1=2 Circle with the radius of 8:88mm attached to a robotic manipulator. The needle was held by a grasper which is attached to the robotic arm. The experimental results illustrate that the path planned curved needle insertions are fifty percent more accurate than the unplanned ones. The results also show that this open loop approach is sensitive to model parameters.</p> / Master of Applied Science (MASc)

This thesis analyzes the problem of acquiring stereoscopic images in all gazing directions around a reference viewpoint in space with the purpose of creating stereoscopic panoramas of non-static scenes. The generation of immersive stereoscopic imagery suitable to stimulate human stereopsis requires images from two distinct viewpoints with horizontal parallax in all gazing directions, or to be able to simulate this situation in the generated imagery. The available techniques to produce omnistereoscopic imagery for human viewing are not suitable to capture dynamic scenes stereoscopically. This is a not trivial problem when considering acquiring the entire scene at once while avoiding self-occlusion between multiple cameras. In this thesis, the term omnidirectional refers to all possible gazing directions in azimuth and a limited set of directions in elevation. The acquisition of dynamic scenes restricts the problem to those techniques suitable for collecting in one simultaneous exposure all the necessary visual information to recreate stereoscopic imagery in arbitrary gazing directions. The analysis of the problem starts by defining an omnistereoscopic viewing model for the physical magnitude to be measured by a panoramic image sensor intended to produce stereoscopic imagery for human viewing. Based on this model, a novel acquisition model is proposed, which is suitable to describe the omnistereoscopic techniques based on horizontal stereo. From this acquisition model, an acquisition method based on multiple cameras combined with the rendering by mosaicking of partially overlapped stereoscopic images is identified as a good candidate to produce omnistereoscopic imagery of dynamic scenes. Experimental acquisition and rendering tests were performed for different multiple-camera configurations. Furthermore, a mosaicking criterion between partially overlapped stereoscopic images based on the continuity of the perceived depth and the prediction of the location and magnitude of unwanted vertical disparities in the final stereoscopic panorama are two main contributions of this thesis. In addition, two novel omnistereoscopic acquisition and rendering techniques were introduced. The main contributions to this field are to propose a general model for the acquisition of omnistereoscopic imagery, to devise novel methods to produce omnistereoscopic imagery, and more importantly, to contribute to the awareness of the problem of acquiring dynamic scenes within the scope of omnistereoscopic research.

This thesis analyzes the problem of acquiring stereoscopic images in all gazing directions around a reference viewpoint in space with the purpose of creating stereoscopic panoramas of non-static scenes. The generation of immersive stereoscopic imagery suitable to stimulate human stereopsis requires images from two distinct viewpoints with horizontal parallax in all gazing directions, or to be able to simulate this situation in the generated imagery. The available techniques to produce omnistereoscopic imagery for human viewing are not suitable to capture dynamic scenes stereoscopically. This is a not trivial problem when considering acquiring the entire scene at once while avoiding self-occlusion between multiple cameras. In this thesis, the term omnidirectional refers to all possible gazing directions in azimuth and a limited set of directions in elevation. The acquisition of dynamic scenes restricts the problem to those techniques suitable for collecting in one simultaneous exposure all the necessary visual information to recreate stereoscopic imagery in arbitrary gazing directions. The analysis of the problem starts by defining an omnistereoscopic viewing model for the physical magnitude to be measured by a panoramic image sensor intended to produce stereoscopic imagery for human viewing. Based on this model, a novel acquisition model is proposed, which is suitable to describe the omnistereoscopic techniques based on horizontal stereo. From this acquisition model, an acquisition method based on multiple cameras combined with the rendering by mosaicking of partially overlapped stereoscopic images is identified as a good candidate to produce omnistereoscopic imagery of dynamic scenes. Experimental acquisition and rendering tests were performed for different multiple-camera configurations. Furthermore, a mosaicking criterion between partially overlapped stereoscopic images based on the continuity of the perceived depth and the prediction of the location and magnitude of unwanted vertical disparities in the final stereoscopic panorama are two main contributions of this thesis. In addition, two novel omnistereoscopic acquisition and rendering techniques were introduced. The main contributions to this field are to propose a general model for the acquisition of omnistereoscopic imagery, to devise novel methods to produce omnistereoscopic imagery, and more importantly, to contribute to the awareness of the problem of acquiring dynamic scenes within the scope of omnistereoscopic research.

The aim of the work was to put together the list of possible ways to use high resolution image in real estate practice. Photographies are created by stitching more than one image on itself. Further on was developed methodology of working with these images and was made an illustration with detailed description of the procedure for each individual case. For each procedure were proposed possibilities in practical using. For the thesis purposes was conducted real estate and public survey. Based on results of the survey were purposed draft measures to improve internet real estate advertising.

This thesis deals with issues automatic composing panoramic photos from individual photos. Gradually examines the various steps of algorithms and methods used in them, which are used in creating panoramas. It also focuses on the design of the own system based on methods discussed to construct panoramas. This system is implemented using OpenCV library and it is created also a graphical interface using a Qt library. Finally, are in this thesis evaluated outcomes of this designed and implemented system on available datasets.