Person tracking using motion detection and optical flow

Person tracking systems to date have either relied on motion detection or optical flow as a basis for person detection and tracking. As yet, systems have not been developed that utilise both these techniques. We propose a person tracking system that uses both, made possible by a novel hybrid optical flow-motion detection technique that we have developed. This provides the system with two methods of person detection, helping to avoid missed detections and the need to predict position, which can lead to errors in tracking and mistakes when handling occlusion situations. Our results show that our system is able to track people accurately, with an average error less than four pixels, and that our system outperforms the current CAVIAR benchmark system.

Components of learning and assessment in linear algebra

Linear algebra provides theory and technology that are the cornerstones of a range of cutting edge mathematical applications, from designing computer games to complex industrial problems, as well as more traditional applications in statistics and mathematical modelling. Once past introductions to matrices and vectors, the challenges of balancing theory, applications and computational work across mathematical and statistical topics and problems are considerable, particularly given the diversity of abilities and interests in typical cohorts. This paper considers two such cohorts in a second level linear algebra course in different years. The course objectives and materials were almost the same, but some changes were made in the assessment package. In addition to considering effects of these changes, the links with achievement in first year courses are analysed, together with achievement in a following computational mathematics course. Some results that may initially appear surprising provide insight into the components of student learning in linear algebra.

Adaptive optical flow for person tracking

Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.

Data mining for lifetime prediction of metallic components

The ability to accurately predict the lifetime of building components is crucial to optimizing building design, material selection and scheduling of required maintenance. This paper discusses a number of possible data mining methods that can be applied to do the lifetime prediction of metallic components and how different sources of service life information could be integrated to form the basis of the lifetime prediction model

The user query based learning system for lifetime prediction of metallic components

Real-World Data Mining Applications generally do not end up with the creation of the models. The use of the model is the final purpose especially in prediction tasks. The problem arises when the model is built based on much more information than that the user can provide in using the model. As a result, the performance of model reduces drastically due to many missing attributes values. This paper develops a new learning system framework, called as User Query Based Learning System (UQBLS), for building data mining models best suitable for users use. We demonstrate its deployment in a real-world application of the lifetime prediction of metallic components in buildings

Downtime reduction analysis of the Australia Post flat mail optical character reader

Machine downtime, whether planned or unplanned, is intuitively costly to manufacturing organisations, but is often very difficult to quantify. The available literature showed that costing processes are rarely undertaken within manufacturing organisations. Where cost analyses have been undertaken, they generally have only valued a small proportion of the affected costs, leading to an overly conservative estimate. This thesis aimed to develop a cost of downtime model, with particular emphasis on the application of the model to Australia Post’s Flat Mail Optical Character Reader (FMOCR). The costing analysis determined a cost of downtime of $5,700,000 per annum, or an average cost of $138 per operational hour. The second section of this work focused on the use of the cost of downtime to objectively determine areas of opportunity for cost reduction on the FMOCR. This was the first time within Post that maintenance costs were considered along side of downtime for determining machine performance. Because of this, the results of the analysis revealed areas which have historically not been targeted for cost reduction. Further exploratory work was undertaken on the Flats Lift Module (FLM) and Auto Induction Station (AIS) Deceleration Belts through the comparison of the results against two additional FMOCR analysis programs. This research has demonstrated the development of a methodical and quantifiable cost of downtime for the FMOCR. This has been the first time that Post has endeavoured to examine the cost of downtime. It is also one of the very few methodologies for valuing downtime costs that has been proposed in literature. The work undertaken has also demonstrated how the cost of downtime can be incorporated into machine performance analysis with specific application to identifying high costs modules. The outcome of this report has both been the methodology for costing downtime, as well as a list of areas for cost reduction. In doing so, this thesis has outlined the two key deliverables presented at the outset of the research.

Optical absorption and EPR studies on tenorite mineral

Optical absorption and EPR studies of the mineral tenorite, a cupric oxide, which originated from Mexico and contains 54.40 wt% of CuO. EPR spectral results indicate two Cu(II) closely interacting ions to give a d2 type structure. The calculated spin Hamiltonian at Rt and LNT are g = 2.160 and D = 125 G . The intensity of resonance line is not the same in low and high field regions. The optical absorption spectrum is due to Cu(II) which three sets of energies indicating Cu(II) in two independent tetragonal C4v symmetry, in addition to d2 structure of octahedral coordination. The octahedral and tetragonal field parameters are compared with those reported for several other copper containing minerals.