This master thesis deals with tracking the moving object in image. The result of the thesis is designed algorithm which is implemented in the programming language C#. This algorithm improves the functionallity of an existing tracking algorithm.

This master thesis deals with tracking the moving object in image. The result of the thesis is designed algorithm which is implemented in the programming language C#. This algorithm improves the functionallity of an existing tracking algorithm.

This thesis presents methods for improving the detection processing of active sonar systems. Measures to compensate for or even exploit particular characteristics of the detection problem for these systems are considered. Reverberation is the result of scattering of the transmitted signal from non-target features. Multipath and variability are particularly pronounced for underwater sound signals because propagation is very sensitive to spatial and temporal temperature variations. Another problem is the low pulse repetition rate due to the relatively low speed of sound. This low data rate reduces tracking and detection performance. / Reverberation often arises as the sum of many small contributions so that received data has a multivariate Gaussian distribution. Estimating the large numbers of parameters in the distribution requires a lot of data. This data is not available because of the low data rate. Representing the scattering as an autoregressive process reduced the data requirement but at some cost to modelling accuracy. A coupled estimator algorithm is developed to estimate the parameters. Detection performance is compared to other models and estimators that assume Gaussian statistics. / To counter multipath distortion the delays and strength of the paths are estimated using a version of the expectation maximisation (EM) algorithm. The magnitude of path amplitudes is then used to decide if a target is present. The EM algorithm is also suggested as a way to find the likely amplitude of reverberation from a few large scatterers that that form non-Gaussian reverberation. / Non-parametric methods are considered for detection of short duration incoherent signals in a duct. These detectors compare the ranks of the data in a region being tested for target present to another region assumed to have no target. Simulations are used to explore performance and what happens when the independent samples assumption is violated by the presence of reverberation. / More data can improve detection. Exploiting data from multiple transmissions is difficult because the slow speed of sound allows targets to move out of detection cells between transmissions. Tracking the movements of potential targets can counter this problem. The usefulness of Integrated Probabalistic Data Association (IPDA), which calculates a probability of true track as well as track properties, is considered as a detection algorithm. Improvements when multiple receivers are used as well as limitations when sensor positions are uncertain are investigated.

This thesis examines the performance of some dim target detection algorithms in low-SNR imaging scenarios. In the past research, there have been numerous attempts for detection and tracking barely visible targets for military surveillance applications with infrared sensors. In this work, two of these algorithms are analyzed via extensive simulations. In one of these approaches, dynamic programming is exploited to coherently integrate the visible energy of dim targets over possible relative directions, whereas the other method is a Bayesian formulation for which the target likelihood is updated along time to be able to detect a target moving in any direction. Extensive experiments are conducted for these methods by using synthetic image sequences, as well as some real test data. The simulation results indicate that it is possible to detect dim targets in quite low-SNR conditions. Moreover, the performance might further increase, in case of incorporating any a priori information about the target trajectory.

This thesis presents a framework for motor vehicle detection-tracking surveillance systems. Given an optimized object detection template, the feasibility and effectiveness of the methodology is considered for vehicle counting applications, implementing both a filtering operation of false detection, based on the speed variability in each segment of traffic state, and an occlusion handling technique which considers the unusual affine transformation of tracking subspace, as well as its highly fluctuating averaged acceleration data. The result presents the overall performance considering the trade-off relationship between true detection rate and false detection rate. The filtering operation achieved significant success in removing the majority of non-vehicle elements that do not move like a vehicle. The occlusion handling technique employed also improved the systems performance, contributing counts that would otherwise be lost. For all video samples tested, the proposed framework obtained high correct count (>93% correct counting rate) while simultaneously minimizing the false count rate. For future research, the author recommends the use of more sophisticated filters for specific sets of conditions as well as the implementation of discriminative classifier for detecting different occlusion cases.

Interoception, the signalling, processing, and perceptual representation of the visceral organs, together with trait impulsivity are in the present study examined using the Novel Controllability task (Mancinelli et al., 2021) as individual factors in coping behavior in response to stress. The coping process is conceptualized using the model of regulatory flexibility developed by Bonanno and Burton (2013). The results based on a sample of 39 healthy adults (M = 23,64 years, 22f/17m) do not support the hypothesis that the combined UPPS-P constructs are significantly related to interoception. For the coping process, the results suggest that: Negative Urgency is related to a negative initial appraisal of the stressor context leading to coping rigidity, by limiting the repertoire of strategies and the dynamic function of feedback; Positive Urgency is related to a larger dependency on emotions to guide decision making, motivating a “trial-and-error” coping approach; Sensation Seeking is related with an opposing style of emotion-focused coping where diminished threat perception and reduced sensitivity towards stimulus valence motivate a risk-taking approach, likely to pursue stimulation; Lack of Premeditation, the only facet of impulsivity convincingly related to interoception, is speculated to be associated with a dysregulation of interoceptive afferents facilitating a “here-and-now” attentional and coping focus. Despite lacking full support, the potential involvement of interoception as an internal stressor is discussed as a mediator in impulsive behavior, alongside general methodological issues with measuring interoception.

This master thesis deals with the analysis of the current possibilities for object tracking in the image, based on which is designed a procedure for creating a system capable of tracking an object of interest. Part of this work is designing virtual reality for the needs of implementation of the tracking system, which is finally deployed and tested on a real prototype of unmanned vehicle.