In this master thesis, the problem of tracking groups using an image sequence dataset is examined. Target tracking can be defined as the problem of estimating a target's state given prior knowledge ...about its motion and some sensor measurements related to the target's state. A popular method for target tracking is e.g. the Kalman filter. However, the Kalman filter is insufficient when there are multiple targets in the scene. Consequently, alternative multitarget tracking methods must be applied along with methods for estimating the number of targets in the scene. Multitarget tracking can however be difficult when there are many unresolved targets, e.g. associating observations with targets in dense crowds. A viable simplification is group target tracking, keeping track of groups rather than individual targets. Furthermore, group target tracking is preferred when the user wants to know the motion and extension of a group in e.g. evacuation scenarios. To solve the problem of group target tracking in video surveillance, a combination of GM-PHD filtering and mean shift clustering is proposed. The GM-PHD filter is an approximation of Bayes multitarget filter. Pedestrian detections converted into flat world coordinates from the image dataset are used as input to the filter. The output of the GM-PHD filter consists of Gaussian mixture components with corresponding mean state vectors. The components are divided into groups by using mean shift clustering. An estimate of the number of members and group shape is presented for each group. The method is evaluated using both single camera measurements and two cameras partly surveilling the same area. The results are promising and present a nice visual representation of the groups' characteristics. However, using two cameras gives no improvement in performance, probably due to differences in detections between the two cameras, e.g. a single pedestrian can be observed being at two positions several meters apart making it difficult to determine if it is a single pedestrian or multiple pedestrians.
A GM-PHD filter is used for pedestrian tracking in a crowd surveillance application. The purpose is to keep track of the different groups over time as well as to represent the shape of the groups and ...the number of people within the groups. Input data to the GM-PHD filter are detections using a state of the art algorithm applied to video frames from the PETS 2012 benchmark data. In a first step, the detections in the frames are converted from image coordinates to world coordinates. This implies that groups can be defined in physical units in terms of distance in meters and speed differences in meters per second. The GM-PHD filter is a Bayesian framework that does not form tracks of individuals. Its output is well suited for clustering of individuals into groups. The results demonstrate that the GM-PHD filter has the capability of estimating the correct number of groups with an accurate representation of their sizes and shapes.
Background:
Septic arthritis (SA) after anterior cruciate ligament reconstruction (ACLR) is a rare yet severe complication. The samples in previous studies have been small and without nationwide ...coverage, making analysis uncertain with a risk of bias. Conclusions to recommend preventive measures are therefore difficult to draw, and it has not been possible to perform a comprehensive risk factor analysis.
Purpose:
To study the incidence of SA after ACLR in a large, nationwide population and to study the risk factors for SA after ACLR.
Study Design:
Case-control study; Level of evidence, 3.
Methods:
All ACLRs, primary and revision, in the Swedish Knee Ligament Registry between 2006 and 2013 were linked with data from the Swedish National Board of Health and Welfare. The incidence of SA events was determined using entries from the day of surgery until 90 days postoperatively based on diagnosis codes and the prescription of antibiotics. All events of SA were verified via a review of medical records. Risk factors were analyzed based on data from the registries. Descriptive statistics were used to describe the findings, while logistic regression analysis was used for the risk analysis.
Results:
The cohort consisted of 26,014 primary and revision ACLRs. During the study period, 298 events of SA (1.1%) were identified. The high-volume units (≥500 ACLRs during the study period) had a distribution of SA between 2 and 47 (0.2%-2.9%). Independent risk factors of SA were male sex (OR, 1.65; 95% CI, 1.28-2.13), operating time ≥70 minutes (OR, 1.83; 95% CI, 1.42-2.36), hamstring tendon autograft (OR, 2.23; 95% CI, 1.21-4.08), and clindamycin as perioperative antibiotic prophylaxis (OR, 1.94; 95% CI, 1.10-3.41).
Conclusion:
The incidence of SA after ACLR in this nationwide cohort was 1.1%. Male sex, hamstring tendon autografts, and a longer operating time were all independent risk factors for SA. The use of clindamycin as perioperative antibiotic prophylaxis was a risk factor compared with the use of cloxacillin. Some high-volume units had a very low infection rate (0.2%).
This paper presents a fast, pipelined and scalable hardware architecture for inverting complex valued matrices. The matrix inversion algorithm involves, a QR-factorization based on the squared Givens ...rotations algorithm, the application of a recurrence algorithm for inversion of an upper triangular matrix R, and a matrix multiplication of R/sup -1/ with Q. We show that traditional triangular array architectures employing O(n/sup 2/) communicating processors can be mapped onto a scalable linear array architecture with only O(n) processors. The linear array architecture avoids drawbacks such as non-scalability, large area consumption and low throughput rate. The architecture is implemented using arithmetic operations with 12 bit fixed-point representation. The hardware implementation will be used as a core processor in a real-time smart antenna system.
We herein formulate the concept of a generalized lock-in amplifier for the precision measurement of high frequency signals based on digital cavities. Accurate measurement of signals higher than 200 ...MHz using the generalized lock-in is demonstrated. The technique is compared with a traditional lock-in and its advantages and limitations are discussed. We also briefly point out how the generalized lock-in can be used for precision measurement of giga-hertz signals by using parallel processing of the digitized signals.
Generalized lock-in amplifiers use digital cavities with Q-factors as high as 5X10^8. In this letter, we show that generalized lock-in amplifiers can be used to analyze microwave (giga-hertz) signals ...with a precision of few tens of hertz. We propose that the physical changes in the medium of propagation can be measured precisely by the ultra-high precision measurement of the signal. We provide evidence to our proposition by verifying the Newton's law of cooling by measuring the effect of change in temperature on the phase and amplitude of the signals propagating through two calibrated cables. The technique could be used to precisely measure different physical properties of the propagation medium, for example length, resistance, etc. Real time implementation of the technique can open up new methodologies of in-situ virtual metrology in material design.
In this paper a fixed-point implementation of robust complex valued divider architecture is presented. The architecture uses feedback loops and time multiplexing strategies resulting in a fast and ...area conservative architecture. The architecture has good numerical properties and the result is accurate to less than one ulp. A combination of low latency and high throughput rate makes the architecture ideal for modern high speed signal processing applications. The complex valued divider architecture was implemented and tested on a Xilinx Virtex-II FPGA, clocked at 100MHz, and can easily be ported to an ASIC. The FPGA implementation is used as a core component in a matrix inversion implementation.
Signal processing and communications algorithms often involve computationally demanding manipulations of large complex valued matrices such as matrix inversion. This paper presents a novel, scalable, ...and compact matrix inversion architecture for inverting complex valued matrices based on QR-factorization via the squared Givens rotations algorithm. We show that the traditional triangular array architectures employing O(n 2 ) communicating processors can be mapped onto a single processor thus avoiding large area consumption. The architecture is implemented using arithmetic operations with a 16bit fixed-point representation and has good numerical accuracy. The hardware architecture has been implemented in an FPGA clocked at 100 MHz and will be used as a core processor in a real-time Capon beamforming system.
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