Multiperspective mosaics and layered representation for scene visualization

This thesis documents the efforts made to implement multiperspective mosaicking for the purpose of mosaicking undervehicle and roadside sequences. For the undervehicle sequences, it is desired to create a large, high-resolution mosaic that may used to quickly inspect the entire scene shot by a camera making a single pass underneath the vehicle. Several constraints are placed on the video data, in order to facilitate the assumption that the entire scene in the sequence exists on a single plane. Therefore, a single mosaic is used to represent a single video sequence. Phase correlation is used to perform motion analysis in this case. For roadside video sequences, it is assumed that the scene is composed of several planar layers, as opposed to a single plane. Layer extraction techniques are implemented in order to perform this decomposition. Instead of using phase correlation to perform motion analysis, the Lucas-Kanade motion tracking algorithm is used in order to create dense motion maps. Using these motion maps, spatial support for each layer is determined based on a pre-initialized layer model. By separating the pixels in the scene into motion-specific layers, it is possible to sample each element in the scene correctly while performing multiperspective mosaicking. It is also possible to fill in many gaps in the mosaics caused by occlusions, hence creating more complete representations of the objects of interest. The results are several mosaics with each mosaic representing a single planar layer of the scene

SYMPA, a dedicated instrument for Jovian Seismology. II. Real performance and first results

Context. Due to its great mass and its rapid formation, Jupiter has played a crucial role in shaping the Solar System. The knowledge of its internal structure would strongly constrain the solar system formation mechanism. Seismology is the most efficient way to probe directly the internal structure of giant planets. Aims. SYMPA is the first instrument dedicated to the observations of free oscillations of Jupiter. Principles and theoretical performance have been presented in paper I. This second paper describes the data processing method, the real instrumental performance and presents the first results of a Jovian observation run, lead in 2005 at Teide Observatory. Methods. SYMPA is a Fourier transform spectrometer which works at fixed optical path difference. It produces Doppler shift maps of the observed object. Velocity amplitude of Jupiter's oscillations is expected below 60 cm/s. Results Despite light technical defects, the instrument demonstrated to work correctly, being limited only by photon noise, after a careful analysis. A noise level of about 12 cm/s has been reached on a 10-night observation run, with 21 % duty cycle, which is 5 time better than previous similar observations. However, no signal from Jupiter is clearly highlighted.Comment: 13 pages, 26 figure

Computers in Biology and Medicine / Survey on computer aided decision support for diagnosis of celiac disease

Celiac disease (CD) is a complex autoimmune disorder in genetically predisposed individuals of all age groups triggered by the ingestion of food containing gluten. A reliable diagnosis is of high interest in view of embarking on a strict gluten-free diet, which is the CD treatment modality of first choice. The gold standard for diagnosis of CD is currently based on a histological confirmation of serology, using biopsies performed during upper endoscopy. Computer aided decision support is an emerging option in medicine and endoscopy in particular. Such systems could potentially save costs and manpower while simultaneously increasing the safety of the procedure. Research focused on computer-assisted systems in the context of automated diagnosis of CD has started in 2008. Since then, over 40 publications on the topic have appeared. In this context, data from classical flexible endoscopy as well as wireless capsule endoscopy (WCE) and confocal laser endomicrosopy (CLE) has been used. In this survey paper, we try to give a comprehensive overview of the research focused on computer-assisted diagnosis of CD.FWF 24366(VLID)223161

Design of a High-Speed Architecture for Stabilization of Video Captured Under Non-Uniform Lighting Conditions

Video captured in shaky conditions may lead to vibrations. A robust algorithm to immobilize the video by compensating for the vibrations from physical settings of the camera is presented in this dissertation. A very high performance hardware architecture on Field Programmable Gate Array (FPGA) technology is also developed for the implementation of the stabilization system. Stabilization of video sequences captured under non-uniform lighting conditions begins with a nonlinear enhancement process. This improves the visibility of the scene captured from physical sensing devices which have limited dynamic range. This physical limitation causes the saturated region of the image to shadow out the rest of the scene. It is therefore desirable to bring back a more uniform scene which eliminates the shadows to a certain extent. Stabilization of video requires the estimation of global motion parameters. By obtaining reliable background motion, the video can be spatially transformed to the reference sequence thereby eliminating the unintended motion of the camera. A reflectance-illuminance model for video enhancement is used in this research work to improve the visibility and quality of the scene. With fast color space conversion, the computational complexity is reduced to a minimum. The basic video stabilization model is formulated and configured for hardware implementation. Such a model involves evaluation of reliable features for tracking, motion estimation, and affine transformation to map the display coordinates of a stabilized sequence. The multiplications, divisions and exponentiations are replaced by simple arithmetic and logic operations using improved log-domain computations in the hardware modules. On Xilinx\u27s Virtex II 2V8000-5 FPGA platform, the prototype system consumes 59% logic slices, 30% flip-flops, 34% lookup tables, 35% embedded RAMs and two ZBT frame buffers. The system is capable of rendering 180.9 million pixels per second (mpps) and consumes approximately 30.6 watts of power at 1.5 volts. With a 1024×1024 frame, the throughput is equivalent to 172 frames per second (fps). Future work will optimize the performance-resource trade-off to meet the specific needs of the applications. It further extends the model for extraction and tracking of moving objects as our model inherently encapsulates the attributes of spatial distortion and motion prediction to reduce complexity. With these parameters to narrow down the processing range, it is possible to achieve a minimum of 20 fps on desktop computers with Intel Core 2 Duo or Quad Core CPUs and 2GB DDR2 memory without a dedicated hardware

Surface analysis and fingerprint recognition from multi-light imaging collections

Multi-light imaging captures a scene from a fixed viewpoint through multiple photographs, each of which are illuminated from a different direction. Every image reveals information about the surface, with the intensity reflected from each point being measured for all lighting directions. The images captured are known as multi-light image collections (MLICs), for which a variety of techniques have been developed over recent decades to acquire information from the images. These techniques include shape from shading, photometric stereo and reflectance transformation imaging (RTI). Pixel coordinates from one image in a MLIC will correspond to exactly the same position on the surface across all images in the MLIC since the camera does not move. We assess the relevant literature to the methods presented in this thesis in chapter 1 and describe different types of reflections and surface types, as well as explaining the multi-light imaging process. In chapter 2 we present a novel automated RTI method which requires no calibration equipment (i.e. shiny reference spheres or 3D printed structures as other methods require) and automatically computes the lighting direction and compensates for non-uniform illumination. Then in chapter 3 we describe our novel MLIC method termed Remote Extraction of Latent Fingerprints (RELF) which segments each multi-light imaging photograph into superpixels (small groups of pixels) and uses a neural network classifier to determine whether or not the superpixel contains fingerprint. The RELF algorithm then mosaics these superpixels which are classified as fingerprint together in order to obtain a complete latent print image, entirely contactlessly. In chapter 4 we detail our work with the Metropolitan Police Service (MPS) UK, who described to us with their needs and requirements which helped us to create a prototype RELF imaging device which is now being tested by MPS officers who are validating the quality of the latent prints extracted using our technique. In chapter 5 we then further developed our multi-light imaging latent fingerprint technique to extract latent prints from curved surfaces and automatically correct for surface curvature distortions. We have a patent pending for this method

Optical Coherence Tomography guided Laser-Cochleostomy

Despite the high precision of laser, it remains challenging to control the laser-bone ablation without injuring the underlying critical structures. Providing an axial resolution on micrometre scale, OCT is a promising candidate for imaging microstructures beneath the bone surface and monitoring the ablation process. In this work, a bridge connecting these two technologies is established. A closed-loop control of laser-bone ablation under the monitoring with OCT has been successfully realised

Intelligent tracking of handball players at F.C. Porto and FADEUP

Tese de Mestrado Integrado. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 201