Efficient Point-Based Rendering Using Image Reconstruction

Circular SAR (CSAR) has the ability of 3-D imaging due to its special curve trajectory. Single-pass CSAR can theoretically obtain the resolution of the sub-wavelength level on the distance-azimuth plane, but its resolution at the elevation direction is very low. At the same time, CSAR 3-D imaging with Back Projection(BP) has high algorithm complexity and low imaging efficiency. A coherent 3-D imaging method for multi-circular SAR based on an improved 3-D back projection algorithm is proposed. For the problem of high time complexity of the imaging algorithm, an improved 3-D BP algorithm for CSAR based on constructing geometric interpolation kernel is proposed. 3-D interpolation operations are transformed into 1-D interpolation operations and distance vector searching operations. The final imaging result is obtained by coherently accumulating the improved 3-D BP results of multi-circular SAR. The proposed method solves effectively the problem of low elevation resolution of single-pass CSAR, improves 3-D imaging details, and reduces greatly the time of CSAR 3-D imaging simultaneously. The simulated 3-D imaging results of the conical target and GOTCHA data set from the US Air Force Laboratory verify the effectiveness of the proposed method.

We describe the operational principles of a scalable hardware accelerator for volume rendering. The basic philosophy is to provide an atomic unit which already provides sophisticated volume graphics at interactive rendering speed. Realtime speed can then be achieved by operating multiple units in parallel. The basic unit consists of just four VLSI chips and the volume memory and thus meets the requirements of a small size and low costs. Nevertheless it provides arbitrary perspective projections (e.g., for walk-throughs), Phong shading, a freely moveable light source, depth-cueing and interactive, non-binary classification (semitransparent display) at a frame rate of about 2.5Hz for 2563 data sets.

This doctoral thesis presents a framework for machine based interpretation of Malaysian Sign Language (MSL). The goal is to explore and develop necessary core algorithms that are capable of recognizing hand signs, based on the monocular/2D visual input of a low-cost hardware (Digital Webcam), without the assistance of visual-markers on hands. Successful hand sign interpretation with the aforementioned constrained visual system is challenging. Economical hardware devices often provide noisy/cluttered raw data with limited useful information. Non-involvement of visual markers imposes the requirement of additional strategies to disambiguate occlusions and background complexities. Natural variations in hand posture/gesture performances further convolute the recognition task. Addressing these challenges require computationally heavy algorithms in image processing, machine learning and pattern recognition. Thus vision-based sign language translator frameworks have to be multifaceted and versatile, in order to address innumerable practical concerns. In this research, hand postures interpretation is achieved by statistical projection methods. Analysis of high dimensional hand shape data is a complex task. Thus reducing dimensions via known projection methods aids in alleviating some of these complexities. Locality Preserving Projection (LPP) has been employed to accomplish this goal, while Principal Component Analysis (PCA) has been used as the benchmark method. Both methods were extensively tested against a hand posture database of 24 alphabet signs from MSL. As for the hand gesture interpretation, parameter-less Gaussian process based machine learning methods are proposed, as an alternative to current status quo. A variation of the Gaussian latent variable model – Gaussian Process Dynamic Model (GPDM) – has been employed for hand gesture interpretation. This has been comparatively studied against the established Hidden Markov Model (HMM). These machine learning methods were thoroughly tested against a hand gesture database of 64 signs from MSL. Grammatical sentence construction offers both intelligible sentences, and a mean of identifying erroneous sign classifications. In this thesis, a proof-of-concept on: use of Context Free Grammar (CFG) in successful parsing of meaningful sentences based on recognised gesture words, and how it can be extended in identifying (and correcting) erroneous sign classifications, is demonstrated with 92 sentences and the output of GPDM gesture classification. The novelty and contribution of this research: this is the first undertaking of markerless vision-based translation for MSL. Both LPP and GPDM are introduced to the sign language research field as an outcome of this investigation. The preliminary study and demonstration of grammatical sentence construction for translated gesture signs, is the first of its kind to the best of author's knowledge.

To fill the vacancy of domestic short focal range digital movie zoom projection lens and to meet the requirement of the market,a digital movie zoom projection lens for 0.65 inch DLP 1.3 K digital movie projector was designed by the mechanical compensation method.It includes the former fixed group,the zoom group,the compensation group and the last fixed group.It is composed of ten glass sphere lenses,and the zoom group is composed of one negative lens,the compensation group is composed of two doublet lenses.The total length of the digital movie zoom projection lens is 170 mm,the full aperture is 70 mm.Its focal length range is 14.5~18.2 mm,F-number is 2,projection ratio range is 0.99∶1~1.23∶1,and the BFL is 32.6 mm.The cam curves were designed with the method of equal interval zoom.The image quality in each focal length is excellent with advantages of simple structure,small size,and low cost,and its cam curves are smooth without cam inflexions and processed easily.

The objective of this research project is to develop a user-friendly and cost-effective interactive input device that allows intuitive and efficient manipulation of 3D objects (6 DoF) in virtual reality (VR) visualization environments with flat projections walls. During this project, it was planned to develop an extended version of a laser pointer with multiple laser beams arranged in specific patterns. Using stationary cameras observing projections of these patterns from behind the screens, it is planned to develop an algorithm for reconstruction of the emitter’s absolute position and orientation in space. Laser pointer concept is an intuitive way of interaction that would provide user with a familiar, mobile and efficient navigation though a 3D environment. In order to navigate in a 3D world, it is required to know the absolute position (x, y and z position) and orientation (roll, pitch and yaw angles) of the device, a total of 6 degrees of freedom (DoF). Ordinary laser-based pointers when captured on a flat surface with a video camera system and then processed, will only provide x and y coordinates effectively reducing available input to 2 DoF only. In order to overcome this problem, an additional set of multiple (invisible) laser pointers should be used in the pointing device. These laser pointers should be arranged in a way that the projection of their rays will form one fixed dot pattern when intersected with the flat surface of projection screens. Images of such a pattern will be captured via a real-time camera-based system and then processed using mathematical re-projection algorithms. This would allow the reconstruction of the full absolute 3D pose (6 DoF) of the input device. Additionally, multi-user or collaborative work should be supported by the system, would allow several users to interact with a virtual environment at the same time. Possibilities to port processing algorithms into embedded processors or FPGAs will be investigated during this project as well.

Knee osteoarthritis is highly prevalent in our country. An early diagnosis is very important to provide an accurate and early treatment, and eventually delay its progression. To compare the diagnostic yield for osteoarthritis of two projections in knee X ray examination. We evaluated 44 knees with conventional (AP weight-bearing, in full extension) and Rosenberg (PA weight-bearing in 45 degrees of flexion) X ray projections in 32 patients (24 women and 8 men), aged 26 to 78 years. All patients were symptomatic at the time of evaluation, with a suspicion of knee osteoarthritis. Both projections were analyzed and compared. Joint space in the lateral compartment with conventional AP weight-bearing and Rosenberg projections were 8.6+/-11.5 mm and 7.8+/-10.9 mm, respectively (NS). The joint space for the medial compartment were 8.2+/-10.9 mm and 6.7+/-8.6 mm, respectively (p <0.05). Rosenberg projection is more sensitive to detect knee joint space narrowing as compared with conventional AP weight-bearing projection, at least in the medial compartment of the knee. Therefore, Rosenberg projection should be included in the initial study of any patient with suspicion of knee osteoarthritis.

We propose a new technique to perform nonuniform to uniform grid conversion: first, interpolate using nonuniform splines, then project the resulting function onto a uniform spline space and finally, resample. We derive a closed form solution to the least-squares approximation problem. Our implementation is computationally exact and works for arbitrary sampling rates. We present examples that illustrate advantages of our projection technique over direct interpolation and resampling. The main benefit is the suppression of aliasing.

This thesis work presents the implementation and validation of image processing problems in hardware to estimate the performance and precision gain. It compares the implementation for the addressed problem on a Field Programmable Gate Array (FPGA) with a software implementation for a General Purpose Processor (GPP) architecture. For both solutions the implementation costs for their development is an important aspect in the validation. The analysis of the flexibility and extendability that can be achieved by a modular implementation for the FPGA design was another major aspect. This work is based upon approaches from previous work, which included the detection of Binary Large OBjects (BLOBs) in static images and continuous video streams [13, 15]. One addressed problem of this work is the tracking of the detected BLOBs in continuous image material. This has been implemented for the FPGA platform and the GPP architecture. Both approaches have been compared with respect to performance and precision. This research project is motivated by the MI6 project of the Computer Vision research group, which is located at the Bonn-Rhein-Sieg University of Applied Sciences. The intent of the MI6 project is the tracking of a user in an immersive environment. The proposed solution is to attach a light emitting device to the user for tracking the created light dots on the projection surface of the immersive environment. Having the center points of those light dots would allow the estimation of the user’s position and orientation. One major issue that makes Computer Vision problems computationally expensive is the high amount of data that has to be processed in real-time. Therefore, one major target for the implementation was to get a processing speed of more than 30 frames per second. This would allow the system to realize feedback to the user in a response time which is faster than the human visual perception. One problem that comes with the idea of using a light emitting device to represent the user, is the precision error. Dependent on the resolution of the tracked projection surface of the immersive environment, a pixel might have a size in cm2. Having a precision error of only a few pixels, might lead to an offset in the estimated user’s position of several cm. In this research work the development and validation of a detection and tracking system for BLOBs on a Cyclone II FPGA from Altera has been realized. The system supports different input devices for the image acquisition and can perform detection and tracking for five to eight BLOBs. A further extension of the design has been evaluated and is possible with some constraints. Additional modules for compressing the image data based on run-length encoding and sub-pixel precision for the computed BLOB center-points have been designed. For the comparison of the FPGA approach for BLOB tracking a similar implementation in software using a multi-threaded approach has been realized. The system can transmit the detection or tracking results on two available communication interfaces, USB and RS232. The analysis of the hardware solution showed a similar precision for the BLOB detection and tracking as the software approach. One problem is the strong increase of the allocated resources when extending the system to process more BLOBs. With one of the applied target platforms, the DE2-70 board from Altera, the BLOB detection could be extended to process up to thirty BLOBs. The implementation of the tracking approach in hardware required much more effort than the software solution. The design of high level problems in hardware for this case are more expensive than the software implementation. The search and match steps in the tracking approach could be realized more efficiently and reliably in software. The additional pre-processing modules for sub-pixel precision and run-length-encoding helped to increase the system’s performance and precision.

In order to provide better transportation systems, Indonesian Government is planning to develop a new high-speed rail system in Java that will connect two biggest cities in Java Island, Jakarta and Surabaya, with approximately 685 kilometers of entirely new track. This paper reviewed the Indonesian Government’s plan to develop the high-speed rail in term of comparison to existing modes of transport. This study employs demands projection of high-speed rail using JETRO method and benchmarking from other countries’ high speed rails. Furthermore, air pollution caused by transport mode was calculated based on the emission factor from CACP & CNT. The last is generalized cost that considers total time to travel as value of money. It can be concluded that journey time and fare of the high-speed rail is very competitive to the air transport in Jakarta-Surabaya corridor. The journey time to travel from Jakarta to Surabaya is 4 hours and 19 minutes by high-speed train and 4 hours and 40 minutes by air. Based on the benchmarking analysis, the suitable fare for the high-speed rail should be 70% of the air transport. This study predicted that 61% of air passenger, 18% of conventional rail passenger and 12% of bus passenger will switch to the high-speed rail service in 2020. In total, the high-speed rail will have 24% of market share for the passenger transport and becomes the second largest market share after road transport (52%). The conventional rail and air transport have 14% and 9% of total market share to travel from Jakarta to Surabaya and vice versa. The high-speed rail development reduces carbon emissions caused by transportation systems in Java Island. It has been calculated that there are 2.542 million tonnages of CO2 per annum without introducing high-speed rail, however, the CO2 emissions decrease to 1.694 million tonnages per annum if the high-speed rail is developed in Java Island. Generalized cost of the high-speed rail is higher than road and conventional rail. However, it is lower than air transport. Keywords: Java high-speed rail, HSR Comparison, modal share, journey time

Demographic studies and projections made for the coming years inform about a significant increase ranging from 214 million of elderly people in 1950 to over 1 billion in 2005 i.e. the proportion increased from 8.5% to 13.7 % which would mean that by 2025 one out of every 7 people will be in the Senior category. Seniors are a population with little participation in economic activity and with a substantial increase of leisure time. Moreover, they are likely to suffer different social situations such as abandonment, loneliness, family misunderstanding, lack of social integration, etc. This may lead to an increased consumption of alcohol and licit or illicit drugs, making it an issue that will take new levels of complexity in this new era and must be addressed quickly and conscientiously in the future. In this paper we present a characterization of elderly people admitted to an emergency room, establishing the correlation between violence and alcohol or drug consumption.

The optimal design of information technology systems is a multi-objective problem requiring accurate prediction of both normal and peak loading conditions. The calculation of future peak loading requires the projection of average loading as well as a detailed understanding of parameter interactions. The failure to properly account for cross-source correlations for many component systems can lead to a significant underestimation of the total system variability. We present an IT network model that projects both average and peak loading for a system that is expanding traffic at multiple data sources. The average loading is modeled by independently calculating the traffic growth for all data sources. The future cumulative load distribution is calculated by taking into account historical sources of parameter correlations and scaling to account for future average growth. Finally, the duration of the peak states is calculated by simulating a vector Fractional ARIMA time series model.

Electrical system in the Central Java Province is managed by PT PLN (Persero). The Electrical energy distribution is carried by the APJ (Service Area Network). One of APJ operating in the Central Java Province is APJ Cilacap, APJ Cilacap which is responsible to fulfill the electricity needs in the District of Cilacap and Kebumen. It makes APJ Cilacap as manager of the utility company should be able to provide the energy needs of electricity in both area. In addition of electrical energy demand’s problem, the problems belong to SAIDI, SAIFI and line losses also becomes a problem of electrical energy distribution. Therefore, it needs to have the electrical energy planning so that energy needs, SAIDI, SAIFI and line losses can be known for the following years. In Preparation of Planning estimates that the software used are LEAP (Long Range Energy Planning System) version 2008.0.0.96. In Planning Making using two scenarios namely BAU (Base As Usual) is the result of scenario planning is still the same trend with the growth of base year or there is no policy affected and RPTL PLN which is based on RUPTL PLN (General Planning of Electricity Supply) in period 2012-2016. From the results of planning using LEAP, projected electricity supply, BAU scenario growth in electrical energy consumption, has the average value of customers equal to the Household sector in UPJ Cilacap, Majenang, Sidareja, and Kroya that is 0.41% per year, while the commercial sector, Industrial, and General are 5.39%, 2.33%, 4.60% per year, while UPJ Kebumen and Kroya for each sector 0, 51%, 4.27%, 7.40%, 4.48% per year. While the projections for electricity supply, outage rate index (SAIDI SAIFI), and losses, RPTL PLN scenario of electricity energy consumption growth follows a policy document RUPTL PLN year 2009-2019. Policy scenarios in RPTL PLN where the electrical energy consumption projections estimates the population growth of 0.3% per year, PDRB growth of 4.5% -5.83% per year, Electrification Ratio in 2019 is targeted at 97.5%, and 4.99% growth in connected power per year. For Policy in making electric energy losses in 2019 is targeted at 5.65%. While in making target of outage Index (SAIDI SAIFI) predicted value of SAIDI in the year 2019 at 77,44 minute/consument/years and the value of SAIFI in 2019 by 4,4 times /consument/years. Keyword : Electricity, SAIDI SAIFI, Energy losses, Planning, LEAP

Most of the models for identifying required returns are based on the past performance of profitability, company share prices and market returns. The future expectations seldom get incorporated therein. Govt. expectations are based on different considerations altogether. Lenders also view this aspect differently. Infrastructure projects carried out with or without forming special purpose company pose another set of issues. Practitioners follow different methods & considerations for identifying project required return. These are WACC, CAPM, Risk Adjusted Discount rate, Gordon model, Asset Beta, industry averages, opportunity costs, strategic considerations etc. For a given cost and future projections of project a small upward or downward change in the project required return can make the project financially unattractive or attractive. This is a very grey area of project appraisal. The purpose of this article is to examine the spectrum of issues involved around deciding the hurdle ‘project required return’ and bring out comprehensive view on the same

A novel feature extraction method that utilizes nonlinear mapping from the original data space to the feature space is presented in this dissertation. Feature extraction methods aim to find compact representations of data that are easy to classify. Measurements with similar values are grouped to same category, while those with differing values are deemed to be of separate categories. For most practical systems, the meaningful features of a pattern class lie in a low dimensional nonlinear constraint region (manifold) within the high dimensional data space. A learning algorithm to model this nonlinear region and to project patterns to this feature space is developed. Least squares estimation approach that utilizes interdependency between points in training patterns is used to form the nonlinear region. The proposed feature extraction strategy is employed to improve face recognition accuracy under varying illumination conditions and facial expressions. Though the face features show variations under these conditions, the features of one individual tend to cluster together and can be considered as a neighborhood. Low dimensional representations of face patterns in the feature space may lie in a nonlinear constraint region, which when modeled leads to efficient pattern classification. A feature space encompassing multiple pattern classes can be trained by modeling a separate constraint region for each pattern class and obtaining a mean constraint region by averaging all the individual regions. Unlike most other nonlinear techniques, the proposed method provides an easy intuitive way to place new points onto a nonlinear region in the feature space. The proposed feature extraction and classification method results in improved accuracy when compared to the classical linear representations. Face recognition accuracy is further improved by introducing the concepts of modularity, discriminant analysis and phase congruency into the proposed method. In the modular approach, feature components are extracted from different sub-modules of the images and concatenated to make a single vector to represent a face region. By doing this we are able to extract features that are more representative of the local features of the face. When projected onto an arbitrary line, samples from well formed clusters could produce a confused mixture of samples from all the classes leading to poor recognition. Discriminant analysis aims to find an optimal line orientation for which the data classes are well separated. Experiments performed on various databases to evaluate the performance of the proposed face recognition technique have shown improvement in recognition accuracy, especially under varying illumination conditions and facial expressions. This shows that the integration of multiple subspaces, each representing a part of a higher order nonlinear function, could represent a pattern with variability. Research work is progressing to investigate the effectiveness of subspace projection methodology for building manifolds with other nonlinear functions and to identify the optimum nonlinear function from an object classification perspective.

ALICE is a dedicated heavy-ion experiment at CERN LHC aiming to study the properties of the quark–gluon plasma. A lead– lead collision might produce several ten thousand new particles. Detailed study of the event requires precise measurements of the particle tracks. A 90 m Time Projection Chamber (TPC) with more than 500 000 read-out pads was built as the main central barrel tracker. Collisions can be recorded at a rate of up to about 1 kHz. The front-end electronics, designed from FPGAs and custom ASICs, performs shaping, amplification, digitisation and digital filtering of the signals. The data is forwarded to DAQ via 216 1.25 Gb/s fibre-optical links. Configuration, control and monitoring is done by an embedded Linux system on the front-end electronics. First results on the performance of the front-end electronics and the distributed detector control system are presented. I. TIME PROJECTION CHAMBER (TPC) The A Large Ion Collider Experiment (ALICE) [1] is using a TPC [2] as the main track-finding detector. A TPC is a gaseous detector. It is shaped like an horizontal barrel and positioned in the same direction as the beam pipe, which is passing through the centre of the barrel. The overall length is 500 cm, divided by a 100 kV Central Electrode (CE) into two identical drift volume. The diameter is 494 cm, though the innermost 170 cm is not part of the TPC to make room for the beam pipe and inner tracking detectors. A schematic view of the TPC can be seen in Figure 1. Collisions will take place in the beam pipe in the centre of the TPC, allowing the particles produced to traverse the TPC and leave tracks of ionised gas along their paths. A strong electric field of from the CE will make the electrons drift towards the end planes, where data read-out is performed. Each end plane is divided into 18 azimuthal sectors, which again are divided into two Multi-Wire Proportional Chambers (MWPC), the Outer and Inner Read-Out Chamber (OROC/IROC). The OROC has four Read-out Partitions (RPs); the IROC two. A RP is an electronic entity for reading out data from read-out pads. The ionistic signal will be amplified by the space charge around the wires of the MWPC. The induced charge on the read-out pads is forwarded to the read-out electronics. In total for both sides there are 557568 pads. The drift volume is filled with counting gas composed of 85.7 % Ne, 9.5 % CO2 and 4.8 % N2. A cold, light gas is used to assure low diffusion and low multiple scattering. Field distortions are minimised because of the high ion mobility and few ionisation electrons per unit length. The electronics design noise figure is 1000 RMS e− (700 actually achieved); not limiting the position resolution will require a signal/noise ratio of at least 20. Apart from tracking—measuring the charged particle momentum and having a good two-track separation—it also provides Particle IDentification (PID). The TPC is expected to perform well at multiplicities as high as dNch/dη=8000 in the particle momentum range [0.1, 100] GeV/c and within |η| 90 %, and the dE/dx resolution better than 10 %. Further, the TPC alone will have a momentum resolution of about 1 % at 2 GeV/c and 10 % at 50 GeV/c. For p–p collisions a read-out rate of ≈1 kHz is expected, while for central Pb–Pb collisions ≈0.2 kHz. Figure 1: Schematic view of the TPC. To the left a singe Read-out Partition (RP) is enlarged for visibility. The support for the sectors is shown on the two end planes. Between them is the Central Electrode (CE). The TPC allows space around the centre of the length axis for beam pipe and inner silicon detectors. II. DATA READ-OUT DESIGN As already mentioned, each sector has six RPs. A RP consists of a Read-out Control Unit (RCU) with up to 25 Front-End Cards (FEC), depending on the radial location. The innermost RPs have the highest number of FECs, as a smaller size for the readout-pads is used to increase the resolution to take into account the higher track density close to the collisions. The electronics for one RP, as well as its connection to the central systems is shown as a block diagram in Figure 2. Eight ALICE TPC Read-Out (ALTRO) [3] chips are mounted on a FEC, each capable of reading out 16 read-out pads. The FECs are attached to the RCU via buses; one for data transfer and one for control/monitoring. Once on the RCU, the data is forwarded to Data Acquisition system (DAQ) and the High Level Trigger (HLT) via a 1.25 Gb/s optical fibre. A Detector Control System (DCS) board equipped with an embedded