Deploying speaker verification techniques to vision-based RPA detect and avoid

Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

Crosstalk between the sympathetic nervous system, inflammation and coagulation in gestational diabetes; a therapeutic approach in postmenopausal hypertension

The occurrence of gestational diabetes (GDM) during pregnancy is a powerful sign of a risk of later type 2 diabetes (T2D) and cardiovascular diseases (CVDs). The physiological basis for this disease progression is not yet fully understood, but increasing evidence exists on interplay of insulin resistance, subclinical inflammation, and more recently, on unbalance of the autonomic nervous system. Since the delay in development of T2D and CVD after GDM ranges from years to decades, better understanding of the pathophysiology of GDM could give us new tools for primary prevention. The present study was aimed at investigating the role of the sympathetic nervous system (SNS) in GDM and its associations with insulin and a variety of inflammatory cytokines and coagulation and fibrinolysis markers. This thesis covers two separate study lines. Firstly, we investigated 41 women with GDM and 22 healthy pregnant and 14 non-pregnant controls during the night in hospital. Blood samples were drawn at 24:00, 4:00 and 7:00 h to determine the concentrations of plasma glucose, insulin, noradrenaline (NA) and adrenomedullin, markers of subclinical inflammation, coagulation and fibrinolysis variables and platelet function. Overnight holter ECG recording was performed for analysis of heart rate variability (HRV). Secondly, we studied 87 overweight hypertensive women with natural menopause. They were randomised to use a central sympatholytic agent, moxonidine (0.3mg twice daily), the β-blocking agent atenolol (50 mg once daily+blacebo once daily) for 8 weeks. Inflammatory markers and adiponectin were analysed at the beginning and after 8 weeks. Activation of the SNS (increase in NA, decreased HRV) was seen in pregnant vs. non-pregnant women, but no difference existed between GDM and normal pregnancy. However, modulation (internal rhythm) of HRV was attenuated in GDM. Insulin and inflammatory cytokine levels were comparable in all pregnant women but nocturnal variation of concentrations of C-reactive protein, serum amyloid A and insulin were reduced in GDM. Levels of coagulation factor VIII were lower in GDM compared with normal pregnancy, whereas no other differences were seen in coagulation and fibrinolysis markers. No significant associations were seen between NA and the studied parameters. In the study of postmenopausal women, moxonidine treatment was associated with favourable changes in the inflammatory profile, seen as a decrease in TNFα concentrations (increase in atenolol group) and preservation of adiponectin levels (decrease in atenolol group). In conclusion, our results did not support our hypotheses of increased SNS activity in GDM or a marked association between NA and inflammatory and coagulation markers. Reduced biological variation of HRV, insulin and inflammatory cytokines suggests disturbance of autonomic and hormonal regulatory mechanisms in GDM. This is a novel finding. Further understanding of the regulatory mechanisms could allow earlier detection of risk women and the possibility of prevention. In addition, our results support consideration of the SNS as one of the therapeutic targets in the battle against metabolic diseases, including T2D and CVD.

Coarse-to-fine vision-based localization by indexing scale-invariant features

This paper presents a novel coarse-to-fine global localization approach inspired by object recognition and text retrieval techniques. Harris-Laplace interest points characterized by scale-invariant transformation feature descriptors are used as natural landmarks. They are indexed into two databases: a location vector space model (LVSM) and a location database. The localization process consists of two stages: coarse localization and fine localization. Coarse localization from the LVSM is fast, but not accurate enough, whereas localization from the location database using a voting algorithm is relatively slow, but more accurate. The integration of coarse and fine stages makes fast and reliable localization possible. If necessary, the localization result can be verified by epipolar geometry between the representative view in the database and the view to be localized. In addition, the localization system recovers the position of the camera by essential matrix decomposition. The localization system has been tested in indoor and outdoor environments. The results show that our approach is efficient and reliable. © 2006 IEEE.

Spatial filtering in tone reproduction and vision

This thesis is concerned with spatial filtering. What is its utility in tone reproduction? Does it exist in vision, and if so, what constraints does it impose on the nervous system?

Tone reproduction is just the art and science of taking a picture and then displaying it. The sensors available to capture an image have a greater dynamic range than the media that may be used to display it. Conventionally, spatial filtering is used to boost contrast; it ameliorates the loss of contrast that results when the sensor signal range is scaled down to fit the display range. In this thesis, a type of nonlinear spatial filtering is discussed that results in direct range reduction without range scaling. This filtering process is instantiated in a real-time image processor built using analog CMOS VLSI.

Spatial filtering must be applied with care in both artificial and natural vision systems. It is argued that the nervous system does not simply filter linearly across an image. Rather, the way that we see things implies that the nervous system filters nonlinearly. Further, many models for color vision include a high-pass filtering step in which the DC information is lost. A real-time study of filtering in color space leads to the conclusion that the nervous system is not that simple, and that it maintains DC information by referencing to white.

Dissecting neural circuits for vision in nonhuman primates using fMRI-guided electrophysiology and optogenetics

The visual system is a remarkable platform that evolved to solve difficult computational problems such as detection, recognition, and classification of objects. Of great interest is the face-processing network, a sub-system buried deep in the temporal lobe, dedicated for analyzing specific type of objects (faces). In this thesis, I focus on the problem of face detection by the face-processing network. Insights obtained from years of developing computer-vision algorithms to solve this task have suggested that it may be efficiently and effectively solved by detection and integration of local contrast features. Does the brain use a similar strategy? To answer this question, I embark on a journey that takes me through the development and optimization of dedicated tools for targeting and perturbing deep brain structures. Data collected using MR-guided electrophysiology in early face-processing regions was found to have strong selectivity for contrast features, similar to ones used by artificial systems. While individual cells were tuned for only a small subset of features, the population as a whole encoded the full spectrum of features that are predictive to the presence of a face in an image. Together with additional evidence, my results suggest a possible computational mechanism for face detection in early face processing regions. To move from correlation to causation, I focus on adopting an emergent technology for perturbing brain activity using light: optogenetics. While this technique has the potential to overcome problems associated with the de-facto way of brain stimulation (electrical microstimulation), many open questions remain about its applicability and effectiveness for perturbing the non-human primate (NHP) brain. In a set of experiments, I use viral vectors to deliver genetically encoded optogenetic constructs to the frontal eye field and faceselective regions in NHP and examine their effects side-by-side with electrical microstimulation to assess their effectiveness in perturbing neural activity as well as behavior. Results suggest that cells are robustly and strongly modulated upon light delivery and that such perturbation can modulate and even initiate motor behavior, thus, paving the way for future explorations that may apply these tools to study connectivity and information flow in the face processing network.

Food preference and intake pattern of Penaeus monodon (Fab.) in semi-intensive culture system

P. monodon juveniles prefer natural food than artificial feed in their initial stage of rearing. However, the percentage preference towards artificial feed increases as the days of culture/average body weight increases. Consumption of artificial feed was high during evening meal (1700h) and low during night meal (2200h). The index of intestine fullness was high (8.4±0.7) during initial stage of rearing, compared to that of final stage of rearing (4.9±0.4), probably due to low nutritional value of intake material and low water depth at initial stage. At all stage of rearing omnivorous feeding habit was established and no evidence of diet periodicity in feeding activity was observed.

A vision-based remote control

This Chapter presents a vision-based system for touch-free interaction with a display at a distance. A single camera is fixed on top of the screen and is pointing towards the user. An attention mechanism allows the user to start the interaction and control a screen pointer by moving their hand in a fist pose directed at the camera. On-screen items can be chosen by a selection mechanism. Current sample applications include browsing video collections as well as viewing a gallery of 3D objects, which the user can rotate with their hand motion. We have included an up-to-date review of hand tracking methods, and comment on the merits and shortcomings of previous approaches. The proposed tracker uses multiple cues, appearance, color, and motion, for robustness. As the space of possible observation models is generally too large for exhaustive online search, we select models that are suitable for the particular tracking task at hand. During a training stage, various off-the-shelf trackers are evaluated. From this data differentmethods of fusing them online are investigated, including parallel and cascaded tracker evaluation. For the case of fist tracking, combining a small number of observers in a cascade results in an efficient algorithm that is used in our gesture interface. The system has been on public display at conferences where over a hundred users have engaged with it. © 2010 Springer-Verlag Berlin Heidelberg.

Automated vision tracking of project related entities

Tracking of project related entities such as construction equipment, materials, and personnel is used to calculate productivity, detect travel path conflicts, enhance the safety on the site, and monitor the project. Radio frequency tracking technologies (Wi-Fi, RFID, UWB) and GPS are commonly used for this purpose. However, on large-scale sites, deploying, maintaining and removing such systems can be costly and time-consuming. In addition, privacy issues with personnel tracking often limits the usability of these technologies on construction sites. This paper presents a vision based tracking framework that holds promise to address these limitations. The framework uses videos from a set of two or more static cameras placed on construction sites. In each camera view, the framework identifies and tracks construction entities providing 2D image coordinates across frames. Combining the 2D coordinates based on the installed camera system (the distance between the cameras and the view angles of them), 3D coordinates are calculated at each frame. The results of each step are presented to illustrate the feasibility of the framework.