Browsing by Author "Han, Jiwan"

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    A comparison of classification approaches for threat detection in CT based baggage screening
    (IEEE, 2013-02-21) Megherbi, Najla; Han, Jiwan; Breckon, Toby P.; Flitton, Greg T.
    Computed Tomography (CT) based baggage security screening systems are of increasing use in transportation security. The ability to automatically identify potential threat item is a key aspect of current research in this area. Here we present a comparison of varying classification approaches for the automated detection of threat objects in cluttered 3D CT imagery from such security screening systems. By combining 3D medical image segmentation techniques with 3D shape classification and retrieval methods we compare five varying final classification stage approaches and present significant performance achievements in the automated detection of specified exemplar items.
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    Engaging students for the learning and assessment of the advanced computer graphics module using the latest technologies
    (inScience Press, 2017-07) Liu, Yonghuai; Yang, Longzhi; Han, Jiwan; Lu, Bin; Yuen, Peter W. T.; Zhao, Yitian; Song, Ran
    The advanced computer graphics has been one of the most basic and landmark modules in the field of computer science. It usually covers such topics as core mathematics, lighting and shading, texture mapping, colour and depth, and advanced modeling. All such topics involve mathematics for object modeling and transformation, and programming for object visualization and interaction. While some students are not as good in either mathematics or programming, it is usually a challenge to teach computer graphics to these students effectively. This is because it is difficult for students to link mathematics and programming with what they used to see in video games and the TV advertisements for example and thus they can easily be put off. In this paper, we investigate how the latest technologies can help alleviate the teaching and learning tasks. Instead of selecting the low level programming languages for demonstration and assignment such as Java, Java 3D, C++, or OpenGL, we selected Three.js, which is one of the latest and freely accessible 3D graphics libraries. It has a unique advantage that it provides a seamless interface between the main stream web browsers and 2D/3D graphics. The developed code can be run on a web browser such as Firefox, Chrome, or Safari for testing, debugging and visualization without code changing. The unique design patterns and objectives of Three.js can be very attractive to third party software houses to develop auxiliary functions, methods and tutorials and to make them freely available for the public. Such a unique property of Three.js and its widely available supporting resources are especially helpful to engage students, inspire their learning and facilitate teaching. To evaluate the effectiveness for using Three.js in teaching computer graphics we have set up an assignment for scene modeling in the last 4 years with focuses on the quality of the simulated scene (50%) and the quality of the assignment report (50%). We have evaluated different assessment forms of the module that we taught in the last four years: in 2013-2014 the module consisted of 20% assignment and 80% exam based on Java 3D; in 2014-2015 the same proportion of assignment/exam but based on WebGL, in 2015-2016 the module was 50-50% of assignment and exam but based on Three.js; and in this year the module is 100% assignment based on Three.js. The effectiveness of the module delivery has been evaluated both qualitatively and quantitatively from five aspects: a) average marks of students, b) moderator report, c) module evaluation questionnaire, d) external examiner’s comments and e) examination board recommendations. The results have shown that Three.js is indeed more successful in engaging students for learning and the 100% assignment assessment enables students to focus more on the design and development. This four year result is really encouraging to us as an educational institute to embrace the latest technologies for the delivery of such challenging modules as computer graphics and machine learning.
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    Real-time people and vehicle detection from UAV imagery
    (2011-01-24T00:00:00Z) Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan; Röning, J.; Casasent, D. P.; Hall, E. L.
    A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle(UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance andsurveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trainedcascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approachfor people detection in thermal imagery based on a similar cascaded classification technique combining additionalmultivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people undervarying conditions in both isolated rural and cluttered urban environments with minimal false positive detection.Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each objectof interest (vehicle/ person) at least once in the environment (i.e. per search patter flight path) rather than every object ineach image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic objectdetection rate for each flight pattern exceeds 90%.