Design, implementation and evaluation of automated surveillance systems

El reconocimiento de patrones ha conseguido un nivel de complejidad que nos permite reconocer diferente tipo de eventos, incluso peligros, y actuar en concordancia para minimizar el impacto de una situación complicada y abordarla de la mejor manera posible. Sin embargo, creemos que todavía se puede llegar a alcanzar aplicaciones más eficientes con algoritmos más precisos. Nuestra aplicación quiere probar a incluir el nuevo paradigma de la programación, las redes neuronales. Nuestra idea en principio fue explorar la alternativa que las nuevas redes neuronales convolucionales aportaban, en donde se podía ver en vídeos de ejemplos la alta tasa de detección e identificación que, por ejemplo, YOLOv2 podría mostrar. Después de comparar las características, vimos que YOLOv3 ofrecía un buen balance entre precisión y rapidez como comentaremos más adelante. Debido a la tasa de baja detecciones, haremos uso de los filtros de Kalman para ayudarnos a la hora de hacer reidentificación de personas y objetos. En este proyecto, haremos un estudio además de las alternativas de videovigilancia con las que cuentan empresas del sector y veremos que clase de productos ofrecen y, por otro lado, observaremos cuales son los trabajos de los grupos de investigadores de otras universidades que más similitudes tienen con nuestro objetivo. Dedicaremos, por lo tanto, el uso de esta red neuronal para detectar eventos como el abandono de mochilas y para mostrar la densidad de tránsito en localizaciones concretas, así como utilizaremos una metodología más tradicional, el flujo óptico, para detectar actuaciones anormales en una multitud.Automatic surveillance system is getting more and more sophisticated with the increasing calculation power that computers are reaching. The aim of this project is to take advantage of these tools and with the new classification and detection technology brought by neural networks, develop a surveillance application that can recognize certain behaviours (which are the detection of lost backpacks and suitcases, detection of abnormal crowd activity and heatmap of density occupation). To develop this program, python has been the selected programming language used, where YOLO and OpenCV form the spine of this project. After testing the code, it has been proved that due to the constrains of the detection for small objects, the project does not perform as it should for real development, but still it shows potential for the detection of lost backpacks in certain videos from the GBA dataset [1] and PETS2006 dataset [2]. The abnormal activity detection for crowds is made with a simple algorithm that seems to perform well, detecting the anomalies in all the testing dataset used, generated by the University of Minnesota [3]. Finally, the heatmap can display correctly the projection of people on the ground for five second, just as intended. The objective of this software is to be part of the core of what could be a future application with more modules that will be able to perform full automated surveillance tasks and gather useful information data, and these advances and future proposal will be explained in this memory.Máster Universitario en Ingeniería Industrial (M141

Screenomics : a new approach for observing and studying individuals' digital lives

This study describes when and how adolescents engage with their fast-moving and dynamic digital environment as they go about their daily lives. We illustrate a new approach—screenomics—for capturing, visualizing, and analyzing screenomes, the record of individuals’ day-to-day digital experiences. Sample includes over 500,000 smartphone screenshots provided by four Latino/Hispanic youth, age 14 to 15 years, from low-income, racial/ethnic minority neighborhoods. Screenomes collected from smartphones for 1 to 3 months, as sequences of smartphone screenshots obtained every 5 seconds that the device is activated, are analyzed using computational machinery for processing images and text, machine learning algorithms, human labeling, and qualitative inquiry. Adolescents’ digital lives differ substantially across persons, days, hours, and minutes. Screenomes highlight the extent of switching among multiple applications, and how each adolescent is exposed to different content at different times for different durations—with apps, food-related content, and sentiment as illustrative examples. We propose that the screenome provides the fine granularity of data needed to study individuals’ digital lives, for testing existing theories about media use, and for generation of new theory about the interplay between digital media and development

An improved classification approach for echocardiograms embedding temporal information

Cardiovascular disease is an umbrella term for all diseases of the heart. At present, computer-aided echocardiogram diagnosis is becoming increasingly beneficial. For echocardiography, different cardiac views can be acquired depending on the location and angulations of the ultrasound transducer. Hence, the automatic echocardiogram view classification is the first step for echocardiogram diagnosis, especially for computer-aided system and even for automatic diagnosis in the future. In addition, heart views classification makes it possible to label images especially for large-scale echo videos, provide a facility for database management and collection. This thesis presents a framework for automatic cardiac viewpoints classification of echocardiogram video data. In this research, we aim to overcome the challenges facing this investigation while analyzing, recognizing and classifying echocardiogram videos from 3D (2D spatial and 1D temporal) space. Specifically, we extend 2D KAZE approach into 3D space for feature detection and propose a histogram of acceleration as feature descriptor. Subsequently, feature encoding follows before the application of SVM to classify echo videos. In addition, comparison with the state of the art methodologies also takes place, including 2D SIFT, 3D SIFT, and optical flow technique to extract temporal information sustained in the video images. As a result, the performance of 2D KAZE, 2D KAZE with Optical Flow, 3D KAZE, Optical Flow, 2D SIFT and 3D SIFT delivers accuracy rate of 89.4%, 84.3%, 87.9%, 79.4%, 83.8% and 73.8% respectively for the eight view classes of echo videos

Identification and Characterization of Mitochondrial DNA Variants in Alzheimer\u27s Disease

Alzheimer\u27s Disease (AD) is a complex neurodegenerative disorder that affects a significant portion of the human population regardless of ethnicity or gender. A mitochondrial hypothesis of AD has been proposed based on a number of studies which establish altered oxidative phosphorylation (OXPHOS) and ATP synthesis in AD tissue. ATP demand is most prevalent in the brain; damage to OXPHOS could severely impair brain metabolism, thereby leading to a decline in cognitive function. Four out of five complexes in the OXPHOS pathway are partly encoded by mitochondrial DNA (mtDNA); thus, this may be a crucial site of lesions that alter brain activity. Within the last decade a number of neuromuscular disorders have been found to be associated with mutations in mtDNA. AD patients share a number of similarities with the mitochondrial encephalomyopathies such as reduced oxidative metabolism, delayed onset of neurological symptoms, and pathological changes that damage tissues with high ATP demand. For these reasons we have been studying AD brain tissue for known, as well as any uncharacterized, mtDNA mutations. We examined brain autopsy tissue for deleted mtDNA by PCR-based methods and Southern analysis. AD brain tissue was obtained from autopsy-confirmed cases. Using a rat brain model system to examine postmortem effects, we found no mtDNA degradation after 30 hours at RT by Southern analysis. We then assessed brain tissue for the 5 kb deletion (\rm mtDNA\sp{\Delta 4977}) by PCR-based methods. While optimizing quantitative techniques we found that serial dilution PCR and kinetic PCR yielded different deletion levels although both methods indicated a greater ratio of \rm mtDNA\sp{\Delta 4977} in the caudate than in the parietal cortex of a cognitively intact control. By serial dilution PCR we determined that AD temporal cortex had a 12 fold greater frequency of \rm mtDNA\sp{\Delta 4977} than controls (0.0628% vs 0.0053%). Using diagnostic restriction enzyme analysis, we detected the previously described point mutation, \rm tRNA\sp{gln4336}, in one Caucasian AD patient and in none of the controls. Biochemical studies indicated that there is a significant decrease in cytochrome c oxidase (COX) activity in platelets and brain tissue of AD patients as well as perturbed COX I, II and III mRNA levels. We examined the mitochondrially encoded COX subunits by single strand conformation polymorphism (SSCP) and DNA sequencing and identified thirty two variants. SSCP efficiency was estimated at 80%. Sixteen of the mutations are new mtDNA variants including a moderately conserved phe- $\u3e$ leu missense change in COX III at np 9861 which was observed in 4.2% (1/24) of the AD patients and in 0% (0/16) of the controls. Further studies will define if this mutation plays any pathogenic role in AD or in COX activity suppression

Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring

More complex image understanding algorithms are increasingly practical in a host of emerging applications. Object tracking has value in surveillance and data farming; and object recognition has applications in surveillance, data management, and industrial automation. In this work we introduce an object recognition application in automated nutritional intake analysis and a tracking application intended for surveillance in low quality videos. Automated food recognition is useful for personal health applications as well as nutritional studies used to improve public health or inform lawmakers. We introduce a complete, end-to-end system for automated food intake measurement. Images taken by a digital camera are analyzed, plates and food are located, food type is determined by neural network, distance and angle of food is determined and 3D volume estimated, the results are cross referenced with a nutritional database, and before and after meal photos are compared to determine nutritional intake. We compare against contemporary systems and provide detailed experimental results of our system\u27s performance. Our tracking systems consider the problem of car and human tracking on potentially very low quality surveillance videos, from fixed camera or high flying \acrfull{uav}. Our agile framework switches among different simple trackers to find the most applicable tracker based on the object and video properties. Our MAPTrack is an evolution of the agile tracker that uses soft switching to optimize between multiple pertinent trackers, and tracks objects based on motion, appearance, and positional data. In both cases we provide comparisons against trackers intended for similar applications i.e., trackers that stress robustness in bad conditions, with competitive results

Trajectory Mining for Movement Ecology of Animals

Tohoku University橋本浩一課

Magnetic resonance imaging in cardiovascular disease

Background Superparamagnetic particles of iron oxide (SPIO) are part of a novel and exciting class of ‘smart’ magnetic resonance imaging (MRI) contrast agents that are taken up by inflammatory cells. Ultrasmall SPIO (USPIO; ~30 nm diameter) can be used to assess cellular tissue inflammation and SPIO (80-150 nm) have the potential to be used to label cells ex vivo for in vivo cell tracking studies. Objectives The aims of the thesis were therefore (i) to develop and validate quantitative MRI methodology for assessing SPIO uptake within tissues, (ii) to demonstrate USPIO accumulation within the aortic wall and its implications in patients with abdominal aortic aneurysms (AAA), and (iii) to develop and apply a Good Manufacturing Practice (GMP) compliant method of SPIO cell labelling in healthy volunteers. Methods Patients with asymptomatic AAA >4.0 cm in diameter were recruited. Imaging sequences were optimised in eight patients using a 3 tesla MRI scanner. Data were analysed using the decay constant for multi echo T2* weighted (T2*W) sequences (T2*) or its inverse (R2*) and the repeatability of these measurements was established. A further twenty-nine patients underwent MRI scanning before and 24- 36 hours after administration of USPIO. T2 and multi echo T2*W sequences were performed and ultrasound-based growth rate data were collected. Operative aortic wall tissue samples were obtained from patients undergoing open surgical aneurysm repair. A GMP compliant protocol was developed for labelling cells with SPIO for clinical cell tracking studies. The effects of SPIO-labelling on cell viability and function were assessed in vitro. A phased-dosing protocol was used to establish the safety of intravenous administration of SPIO-labelled cells in healthy volunteers. The feasibility of imaging cells at a target site in vivo following local or systemic administration was assessed. Tracking of SPIO-labelled cells to a target site was investigated by inducing an iatrogenic inflammatory focus in the skin of the anterior thigh of healthy volunteers, following which autologous SPIO-labelled cells were administered and their accumulation was assessed using MRI scanning and histology of skin biopsies. Results Robust and semi-quantitative data acquisition and image analysis methodology was developed for the assessment of SPIO accumulation in tissues. In patients with AAA, histological analysis of aortic wall tissue samples confirmed USPIO accumulation in areas of cellular inflammation. USPIO-enhanced MRI detected aortic wall inflammation and mural USPIO uptake was associated with a 3-fold higher aneurysm expansion rate. Human mononuclear cells were labelled with SPIO under GMP compliant conditions without affecting cell viability or function. Both local and intravenous administration of SPIO-labelled cells was safe and cells were detectable in vitro and in vivo using a clinical MRI scanner. SPIO-labelled cells tracked to a focal iatrogenic inflammatory focus following intravenous administration in humans and were detectable on MRI scanning and histological examination of skin biopsies. Conclusions SPIO contrast agents have an extensive range of potential clinical applications. USPIO uptake in the wall of AAA appears to identify cellular inflammation and predict accelerated aneurysm expansion. This is therefore a promising investigative tool for stratifying the risk of disease progression in patients with AAA, and may also be considered as a biomarker for response to novel pharmacological agents. The ability to label cells for non-invasive cell tracking studies would facilitate the further development of novel cell-based therapies and would enable assessment of dynamic inflammatory processes through inflammatory cell tracking

Quantitative Phosphoproteomics of Proteasome Inhibition in Multiple Myeloma Cells

BACKGROUND: The proteasome inhibitor bortezomib represents an important advance in the treatment of multiple myeloma (MM). Bortezomib inhibits the activity of the 26S proteasome and induces cell death in a variety of tumor cells; however, the mechanism of cytotoxicity is not well understood. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the differential phosphoproteome upon proteasome inhibition by using stable isotope labeling by amino acids in cell culture (SILAC) in combination with phosphoprotein enrichment and LC-MS/MS analysis. In total 233 phosphoproteins were identified and 72 phosphoproteins showed a 1.5-fold or greater change upon bortezomib treatment. The phosphoproteins with expression alterations encompass all major protein classes, including a large number of nucleic acid binding proteins. Site-specific phosphopeptide quantitation revealed that Ser38 phosphorylation on stathmin increased upon bortezomib treatment, suggesting new mechanisms associated to bortezomib-induced apoptosis in MM cells. Further studies demonstrated that stathmin phosphorylation profile was modified in response to bortezomib treatment and the regulation of stathmin by phosphorylation at specific Ser/Thr residues participated in the cellular response induced by bortezomib. CONCLUSIONS/SIGNIFICANCE: Our systematic profiling of phosphorylation changes in response to bortezomib treatment not only advanced the global mechanistic understanding of the action of bortezomib on myeloma cells but also identified previously uncharacterized signaling proteins in myeloma cells