Euclidean Calculation of Feature Points of a Rotating Satellite: A Daisy Chaining Approach

The occlusion of feature points and/or feature points leaving the field of view of a camera is a significant practical problem that can lead to degraded performance or instability of visual servo control and vision-based estimation algorithms. By assuming that one knownEuclidean distance between two feature points in an initial view is available, homography relationships and image geometry are used in this paper to determine the Euclidean coordinates of feature points in the field of view. A new daisy-chainingmethod is then used to relate the position and orientation of a plane defined by the feature points to other feature-point planes that are rigidly connected. Through these relationships, the Euclidean coordinates of the original feature points can be tracked even as they leave the field of view. This objective is motivated by the desire to track the Euclidean coordinates of feature points on one face of a satellite as it continually rotates and feature points become self-occluded. A numerical simulation is included to demonstrate that the Euclidean coordinates can be tracked even when they leave the field of view. However, the results indicate the need for amethod to reconcile any accumulated errorwhen the feature points return to thefield of view. Nomenclature A = intrinsic camera-calibration matrix dj = distance to j plane along nj F j, Fj = frames attached to the j and j planes Gj = projective homography matrix of the jth frame Hj = Euclidean homography matrix of the jth frame I = fixed coordinate frame attached to the camera mji, m ji = normalized Euclidean coordinate of the ith feature point of the j and j planes expressed in

Semi-blind robust indentification and robust control approach to personalized anemia management.

The homeostatic blood hemoglobin (Hb) content of a healthy individual varies between the range of 14-18 g/dL for a male and 12-16 g/dL for a female. This quantity provides an estimate of red blood cell (RBC) count in circulation at any given moment. RBC is a protein carrying substance that transports oxygen from the lungs to other tissues in the body and is synthesized by the kidney through a process known as erythropoiesis where erythropoietin is secreted in response to hypoxia. In this regard, the kidneys act not only as a controller but also as a sensor in regulating RBC levels. Patients with chronic kidney diseases (CKD) have dysfunctional kidneys that compromise these fundamental kidney functions. Consequently, anemia is developed. Anemics of CKD have low levels of Hb that must be controlled and properly regulated to the appropriate therapeutic range. Until the discovery of recombinant human erythropoietin (EPO) over three decades ago, treatment procedure of anemia conditions primarily involved repeated blood transfusions–a process known to be associated with several other health related complications. This discovery resulted in a paradigm shift in anemia management from blood transfusions to dosage therapies. The main objective of anemia management with EPO is to increase patients’ hemoglobin level from low to a suitable therapeutic range as defined by the National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (NKF-KDOI) to be in the range of 10 - 12 g/dL while avoiding response values beyond 14 g/dL to prevent other complications associated with EPO medication. It is therefore imperative that clinicians balance dosage efficacy and toxicity in anemia management therapies. At most treatment facilities, protocols are developed to conform to NKF-KDOI recommendations. These protocols are generally based on EPO packet inserts and the expected Hb responses from the average patient. The inevitable variability within the patient group makes this “one-size-fits-all” dosing scheme non-optimal, at best, and potentially dangerous for certain group of patients that do not adhere to the notion of expected “average” response. A dosing strategy that is tailored to the individual patients’ response to EPO medication could provide a better alternative to the current treatment methods. An objective of this work is to develop EPO dosing strategies tailored to the individual patients using robust identification techniques and modern feedback control methods. First, a unique model is developed based on Hb responses and dosage EPO of the individual patients using semi-blind robust identification techniques. This provides a nominal model and a quantitative information on model uncertainty that accounts for other possible patient’s dynamics not considered in the modeling process. This is in the framework of generalized interpolation theory. Then, from the derived nominal model and the associated uncertainty information, robust controller is designed via the =H1-synthesis methods to provide a new dosing strategies for the individual patients. The H1 control theory has a feature of minimizing the influence of some unknown worst case gain disturbance on a system. Finally, a framework is provided to strategize dosing protocols for newly admitted patients

Tracking interacting targets in multi-modal sensors

PhDObject tracking is one of the fundamental tasks in various applications such as surveillance, sports, video conferencing and activity recognition. Factors such as occlusions, illumination changes and limited field of observance of the sensor make tracking a challenging task. To overcome these challenges the focus of this thesis is on using multiple modalities such as audio and video for multi-target, multi-modal tracking. Particularly, this thesis presents contributions to four related research topics, namely, pre-processing of input signals to reduce noise, multi-modal tracking, simultaneous detection and tracking, and interaction recognition. To improve the performance of detection algorithms, especially in the presence of noise, this thesis investigate filtering of the input data through spatio-temporal feature analysis as well as through frequency band analysis. The pre-processed data from multiple modalities is then fused within Particle filtering (PF). To further minimise the discrepancy between the real and the estimated positions, we propose a strategy that associates the hypotheses and the measurements with a real target, using a Weighted Probabilistic Data Association (WPDA). Since the filtering involved in the detection process reduces the available information and is inapplicable on low signal-to-noise ratio data, we investigate simultaneous detection and tracking approaches and propose a multi-target track-beforedetect Particle filtering (MT-TBD-PF). The proposed MT-TBD-PF algorithm bypasses the detection step and performs tracking in the raw signal. Finally, we apply the proposed multi-modal tracking to recognise interactions between targets in regions within, as well as outside the cameras’ fields of view. The efficiency of the proposed approaches are demonstrated on large uni-modal, multi-modal and multi-sensor scenarios from real world detections, tracking and event recognition datasets and through participation in evaluation campaigns