Sharif Digital Repository

Road roughness-induced vibrations are the main source of fatigue damage accumulation in vehicles. Hence, road surface profile modeling and simulation are of high importance when it comes to vehicle fatigue damage assessment. This research focuses on uncovering the statistical distributions that describe the characteristics of road loads that affect fatigue damage accumulation. Particle filtering is deployed to estimate the log-volatility of the road surface profile by assuming a random walk behavior for the hidden log-volatility. The skew-normal distribution with three parameters is fitted to the estimated log-volatility. The inferred parameters are used for synthesizing artificial road... 

Rapid growth of space traffic and small satellite systems for current and future space missions have generated new enhanced performance requirements for navigation subsystem. As such, the navigation subsystem is considered as a vital part of all active satellite systems that effectively influences their successful missions. In this regard, the present work is dedicated on the subject of autonomous satellite navigation utilizing nonlinear filters, for which some laboratory experimentations have also been implemented. Generally, advanced orbit and attitude estimation algorithms can effectively compensate for the effect of low cost hardware and sensor packs utilized in microsatellites. In... 

In this work, the in-motion estimation of Euler angles of a strapdown inertial navigation system is studied using a speedometer, as an aided navigation sensor. First, the derivation of governing error equations has been done. Then, the most appropriate heuristic filters available in references have been chosen for this study. Among this filters, unscented particle filter, that has better performance and conditions for the real-time implementation, has been chosen. Then, an innovative solution for improving the performance of this filter is presented. The proposed filter uses particle swarm optimization to resample the particles. The proposed... 

Visual tracking is a classic problem, but is continuously an active area of research, in computer vision. Given a bounding box defining the object of interest (target) in the first frame of a video sequence, the goal of a general tracker is to determine the ob-ject’s bounding box in subsequent frames. Utilizing sparse representation, we propose a robust tracking algorithm to handle challenges such as illumination variation, pose change, and occlusion. Object appearance is modeled using a dictionary composed of target patch images contained in previous frames. In each frame, the target is found from a set of candidates via a likelihood measure that is proportional to the sum of the... 

To overcome challenges such as object appearance changes and environment illumination variations in tracking methods, online algorithms are suggested to be used instead of offline ones. Online algorithms update the model by the information acquired in the last processed frame. The main challenge of using online algorithms is the accumulation of small errors after several steps of updating of the model (drift) which disturbs the model and causes tracking failure. Using the object information in the first frame in each update can be considered as a solution. The proposed online semi-supervised boosting algorithms can overcome the drift problem at the expense of decreasing their capabilities in... 

Over the past years, several approaches have been used for navigation. Along with the advancement of technology, complicated navigation systems such as inertial navigation system and global positioning system have been employed. These navigation systems have their own strengths and weaknesses. To improve overall system performance they are integrated together as one system.
Presented research aims at developing the integrated navigation system through particle filters. In this study, after a brief overview of the data integration techniques, several techniques which are more common and have better performance than others are examined. This contribution concentrates on filtering methods... 

Television, radio, newspaper, magazines, and billboards are among the major channels that traditionally place ads, however, the advancement of the Internet enables users to seek information online. In display and mobile advertising, the most significant technical development in recent years is the growth of Real-Time Bidding (RTB), which facilitates a real-time auction for a display opportunity. Real-time means the auction is per impression and the process usually occurs less than 300 milliseconds before the ad is placed. RTB has fundamentally changed the landscape of the digital media market by scaling the buying process across a large number of available inventories among publishers in an... 

In this study pain level estimation using facial expression is investigated. To do this, there are two approaches, one approach is sequence level pain estimation and the other one is frame level pain estimation. In sequence level, after feature extraction from all frames of sequence, each sequence is represented by a fixed length feature vector, this feature vector is constructed by concatenating min, max and mean of frame features of that specific sequence, then KLPP is applied in order to reduce feature vector dimension and in the end a linear regression is implemented to predict the pain labels of the sequence. In the frame level, two approaches are introduced, the first one is based on... 

In general, multi-target tracking consists of estimation of the posterior density function of present targets at each scan in the observation area. These targets may have unknown and time varying number of targets. It is a tough job due to misdetections, false alarms, data association ambiguity, and nonlinear equations-non Gaussian noises. These all make it difficult to apply Kalman filter and its extensions such as extended Kalman filter and unscented Kalman filter. Monte Carlo methods, particularly particle filters, have recently aroused the interest of designers and enjoyed a lot of success to deal with multi-target tracking difficulties. In addition, they can handle nonthresholded data... 

The aim of tracking is localization and positioning of position-variant object through consecutive times. The essence of this object determines the application of tracking. For example this object can be the satellite, mobile, certain object in sequential movie or etc. The particle filter as an estimation filter is a method that provides us the solution of tracking Problem. Therefore this thesis is devoted to particle filter and its application in tracking. But tracking problem needs some prior information; one of them is access to measurements relating to object position. In situations that the measurement equation which is related to object position has ambiguity we need another mechanism... 

Human tracking is an essential step in many computer vision-based applications. As single view tracking may not be sufficiently robust and accurate, tracking based on multiple cameras has been widely considered in recent years. This thesis presents a distributed human tracking method in a smart camera network and introduces a particle filter design based on Histogram of Oriented Gradients (HOG) and color histogram. The proposed adaptive motion model also estimates the target speed from the history of its latest displacement and improves the robustness of the tracker by decreasing the probability of missing targets. In addition, a distributed data fusion method is proposed which fuses the... 

In this thesis, Particle Filter Methods are investigated in the context of moving targets tracking and the associated performance analysis. The application scope of this algorithm which is a particular case of Sequential Monte Carlo Method is far broader than tracking of moving targets. This algorithm can be used for mathematical calculations such as estimation of mathematical expectations, integrals, surface area of curves and many other mathematical calculations. In addition, it has applications in other branches of science like genetics. This algorithm is based on random sampling of a probability density function and resampling from the extracted samples. We change this algorithm in... 

Analysis of semen and quality assessments of sperm cells is of great importance in scrutiny of male fertility. Several methods have been introduced for analyzing and identification of the sperm motility and morphology in a semen sample. Identifying and tracking of rapid and variant movements of multiple sperms, in a short duration of time, is somewhat difficult and complex for human, even for an expert. Then applying semi-automated or automated (un-supervised) methods, based on image analysis and computing, spread fast and computer aided semen analyzer systems, became wildly used in clinical and research laboratories.
In this paper we propose an efficient multiple tracking methods to...