233,588 research outputs found
Optimizing Compton camera performance
No full textAmore realistic simulation approach is used to study the behavior of the Compton camera in
this thesis than previous studies to date. The Compton camera differs from gamma cameras
in that the collimator is replaced by a detector known as the ‘scatterer’. Gamma rays may be
Compton scattered in the scatterer and subsequently detected by an ‘absorber’ which is the
equivalent of the detector in a gamma camera. By measuring the energies and the positions
of the points on the scatterer and the absorber where the incident and scattered gamma rays
interacted with the detectors, an image of the source can be reconstructed. Because there is
no collimator present, the potential sensitivity of the Compton camera is much higher than
the gamma camera, resulting in reduced acquisition times.
Most of the work described in this thesis was done with the GEANT4 Monte Carlo
simulation software. GEANT4 has been proven to be very robust and efficient in modelling
physics problems of radiation transport and interactions with matter in complex geometries.
Four major studies are carried out to estimate and optimize the performance of this
novel equipment. The first study takes a look at the scatterer’s imaging parameters with
the aim of prescribing an optimal scatterer material and geometry. In the second study,
the contribution of the absorber to the overall Compton camera performance is evaluated,
considering detector material, interaction type and geometry. The third study explores the
limitations imposed by the detector energy threshold and dead time on the Compton camera
performance, using a simplified model of the general electronic architecture. An evaluation
of Compton camera for scintimammography was performed in the fourth study. For
this study, three dual-head Compton camera models (Si/CZT, Si/LaBr₃:Ce and Si/NaI(Tl)
Compton cameras) were simulated, and the effect of scintillation photons’ interactions with
the photomultipliers was implemented.
The results show that silicon of about 1 cm thickness would be adequate as the Compton
camera scatterer. Analyses suggest however, that the choice of silicon is not completely
flawless. Doppler broadening for this detector material contributes as much as 7.3 mm
and 2.4 mm to full-width-at-half-maximum (FWHM) image resolution at 140.5 keV and
511 keV respectively. On the other hand, detector spatial resolution which accounts for
the least image degradation at 140.5 keV is found to be the dominant degrading factor
at 511 keV, suggesting that the absorber parameters play major roles in image resolution
at higher diagnostic energies. Findings further suggest that cadmium zinc telluride (CZT)
would be themost suitable detector as the absorber since thematerial demonstrated the highest efficiency and least positioning error due to multiple interactions as well as good spatial
resolution. The inclusion of the energy threshold and detector dead time at 140.5 keV, reduced
the Compton camera detection efficiency by 48% and 17% respectively, but improved
the image resolution from 10.7 mm to 9.5 mm at the source-to-scatterer distance of 5 cm.
At 511 keV, the inclusion of these parameters reduced the efficiency by 6% and 13% respectively,
but made no significant difference on the camera resolution. For a challenging
detection case in scintimammography, 5 mm breast tumours of tumour/background uptakes
of 10:1 and 6:1 at 511 keV were used. The best signal-to-noise ratio (SNR) was attained
for the Si/CZT Compton camera model, with the SNR values of 12.2 and 5.3.
It is therefore envisioned that with an optimal camera geometry, improved reconstruction
technique and adequate filter algorithm, the combination of Si and CZT as the scatterer
and the absorber of the Compton camera would make a very promising imaging system for
nuclear medicine studies at higher gamma ray energies where the collimated SPECT systems
perform very poorly due to increased septal penetration. It is equally evident from the
studies that with improved technology, new detectors such as LaBr₃:Ce could replace the
traditional NaI(Tl) detector as imaging detectors
More Accurate Pinhole Camera Calibration with Imperfect Planar Target
No full textThis paper presents a novel approach to camera calibration that improves final accuracy with respect to standard methods using precision planar targets, even if now inaccurate, unmeasured, roughly planar targets can be used. The work builds on a recent trend in camera calibration, namely concurrent optimization of scene structure together with the intrinsic camera parameters. A novel formulation is presented that allows maximum likelihood estimation in the case of inaccurate targets, as it extends the camera extrinsic parameters into a tight parametrization of the whole scene structure. It furthermore observes the special characteristics of multi-view perspective projection of planar targets. Its natural extensions to stereo camera calibration and hand-eye calibration are also presented. Experiments demonstrate improvements in the parametrization of the camera model as well as in eventual stereo reconstruction
Durham All-Sky Camera (DAC)
No full textIn this work, the prototype of a Durham all-sky camera (DAC) was designed and constructed for the purpose of monitoring the night sky of Durham. The DAC consisted of a Fujinon fish-eye lens coupled to a monochrome 640-by-480-pixel CCD camera (DMK-21BF04 model from the ImagingSource) housed in an 8-inch Perspex dome. After construction, the images were taken of the night sky in order to determine the properties of DAC. The field of view of the DAC was 185˚ at average scale of 0.2˚ per pixel.
The astrometric characteristics of the camera were investigated by measuring the relationship between star positions on the 3-D celestial hemisphere and their projected 2-D pixel positions on the DAC CCD images. The derived relationship (the mapping) of the stars onto the CCD images achieved an average uncertainty of 1 pixel. For the reverse process, the uncertainties were 0.2˚ in elevation and 0.7˚ in azimuth. The relationship was tested for the robustness and was found to be stable at the level of 1 pixel.
The photometric characteristics of the camera were studied by investigating how well the magnitude of a star could be measured by DAC. The results showed that, under the sky background condition in Durham, the camera was able to determine a 6th magnitude star at zenith within 1 magnitude uncertainty, but a 4th magnitude star within the similar uncertainty when the stars were at an elevation of 30˚. The brightness of the sky background of Durham was determined to be 18 magnitudes per square arcsecond. Subsequently, the comparison was drawn between the sky background in Durham and in Hawaii, thereby estimating that the accuracy of measuring a 6th magnitude star would be about 7 times better if the camera was deployed under the darker sky background of Hawaii
Automatic camera selection for activity monitoring in a multi-camera system for tennis
No full textIn professional tennis training matches, the coach needs to be able to view play from the most appropriate angle in order to monitor players' activities. In this paper, we describe and evaluate a system for automatic camera selection from a network of synchronised cameras within a tennis sporting arena. This work combines synchronised video streams from multiple cameras into a single summary video suitable for critical review by both tennis players and coaches. Using an overhead camera view, our system automatically determines the 2D tennis-court calibration resulting in a mapping that relates a player's position in the overhead camera to their position and size in another camera view in the network. This allows the system to determine the appearance of a player in each of the other cameras and thereby choose the best view for each player via a novel technique. The video summaries are evaluated in end-user studies and shown to provide an efficient means of multi-stream visualisation for tennis player activity monitoring
Automated camera ranking and selection using video content and scene context
No full textPhDWhen observing a scene with multiple cameras, an important problem to solve is to automatically
identify “what camera feed should be shown and when?” The answer to this question is of interest
for a number of applications and scenarios ranging from sports to surveillance. In this thesis we
present a framework for the ranking of each video frame and camera across time and the camera
network, respectively. This ranking is then used for automated video production. In the first stage
information from each camera view and from the objects in it is extracted and represented in a way
that allows for object- and frame-ranking. First objects are detected and ranked within and across
camera views. This ranking takes into account both visible and contextual information related to
the object. Then content ranking is performed based on the objects in the view and camera-network
level information. We propose two novel techniques for content ranking namely: Routing Based
Ranking (RBR) and Multivariate Gaussian based Ranking (MVG). In RBR we use a rule based
framework where weighted fusion of object and frame level information takes place while in MVG
the rank is estimated as a multivariate Gaussian distribution. Through experimental and subjective
validation we demonstrate that the proposed content ranking strategies allows the identification of
the best-camera at each time.
The second part of the thesis focuses on the automatic generation of N-to-1 videos based on the
ranked content. We demonstrate that in such production settings it is undesirable to have frequent
inter-camera switching. Thus motivating the need for a compromise, between selecting the best
camera most of the time and minimising the frequent inter-camera switching, we demonstrate that
state-of-the-art techniques for this task are inadequate and fail in dynamic scenes. We propose three
novel methods for automated camera selection. The first method (¡go f ) performs a joint optimization
of a cost function that depends on both the view quality and inter-camera switching so that a
i
Abstract ii
pleasing best-view video sequence can be composed. The other two methods (¡dbn and ¡util) include
the selection decision into the ranking-strategy. In ¡dbn we model the best-camera selection
as a state sequence via Directed Acyclic Graphs (DAG) designed as a Dynamic Bayesian Network
(DBN), which encodes the contextual knowledge about the camera network and employs the past
information to minimize the inter camera switches. In comparison ¡util utilizes the past as well
as the future information in a Partially Observable Markov Decision Process (POMDP) where the
camera-selection at a certain time is influenced by the past information and its repercussions in
the future. The performance of the proposed approach is demonstrated on multiple real and synthetic
multi-camera setups. We compare the proposed architectures with various baseline methods
with encouraging results. The performance of the proposed approaches is also validated through
extensive subjective testing
Dual Illumination Planar Doppler Velocimetry using a Single Camera
No full textA Planar Doppler Velocimetry (PDV) illumination system has been designed which
is able to generate two beams, separated in frequency by about 600 MHz. This
allows a common-path imaging head to be constructed, using a single imaging
camera instead of the usual camera pair. Both illumination beams can be derived
from a single laser, using acousto-optic modulators to effect the frequency
shifts. One illumination frequency lies on an absorption line of gaseous iodine,
and the other just off the absorption line. The beams sequentially illuminate a
plane within a seeded flow and Doppler-shifted scattered light passes through an
iodine vapour cell onto the camera. The beam that lies at an optical frequency
away from the absorption line is not affected by passage through the cell, and
provides a reference image. The other beam, the frequency of which coincides
with an absorption line, encodes the velocity information as a variation in
transmission dependent upon the Doppler shift. Images of the flow under both
illumination frequencies are formed on the same camera, ensuring registration of
the reference and signal images. This removes a major problem of a two-camera
imaging head, and cost efficiency is also improved by the simplification of the
system. The dual illumination technique has been shown to operate successfully
with a spinning disc as a test object. The benefits of combining the dual
illumination system with a three-component, fibre-linked imaging head developed
at Cranfield will be discussed
E CHI SE NE FREGA DI MERYL STREEP!
No full textTRADUZIONE DALL'ARABO DI P. D'AMICO, PRESENTAZIONE di I. Camera d'Afflitto - PP. 7-9
Characterization for high dynamic range imaging
No full textIn this paper we present a new practical camera characterization technique to improve color accuracy in high dynamic range (HDR) imaging. Camera characterization refers to the process of mapping device-dependent signals, such as digital camera RAW images, into a well-defined color space. This is a well-understood process for low dynamic range (LDR) imaging and is part of most digital cameras — usually mapping from the raw camera signal to the sRGB or Adobe RGB color space. This paper presents an efficient and accurate characterization method for high dynamic range imaging that extends previous methods originally designed for LDR imaging. We demonstrate that our characterization method is very accurate even in unknown illumination conditions, effectively turning a digital camera into a measurement device that measures physically accurate radiance values — both in terms of luminance and color — rivaling more expensive measurement instruments
Reliable camera motion estimation from compressed MPEG videos using machine learning approach
No full textAs an important feature in characterizing video content, camera motion has been widely applied in various multimedia and computer vision applications. A novel method for fast and reliable estimation of camera motion from MPEG videos is proposed, using support vector machine for estimation in a regression model trained on a synthesized sequence. Experiments conducted on real sequences show that the proposed method yields much improved results in estimating camera motions while the difficulty in selecting valid macroblocks and motion vectors is skipped
Lightweight Agent Framework for Camera Array Applications
No full textThis paper describes a lightweight middleware agent framework (LAF) for coordinating a large array of computers with attached cameras to construct high resolution video-rate image sequences. Compared to existing camera middleware, LAF provides more than a remote sensor access API. The use of an agent framework allows reconfigurable and transparent access to cameras, as well as software agents capable of intelligent processing. It also eases maintenance by encouraging code reuse. Other features include an automatic discovery mechanism at startup, and multiple language bindings. Performance tests showed the lightweight nature of the framework while validating its correctness and scalability. Two different camera agents were implemented to provide access to a large array of distributed cameras. Correct operation of these camera agents was confirmed via several image processing agents
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