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_aJohn Paul D. Ang and Johneric Anselmo B. Razon.
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_aObject motion tracking on a cluttered background: a further enhancement of the condensation algorithm /
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_cJohn Paul D. Ang and Johneric Anselmo B. Razon.
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_cMarch 2005.46
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_a30 pp.
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_atext
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_aunmediated
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_aUndergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2005.
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_aABSTRACT: Almost all people rely on vision to know what is happening in the environment, and with this, it becomes more logical to apply vision as a medium for inputting commands on a computer. Research on computer vision has greatly increase since the last decade due to the need for a more effective medium for interfacing with the a computer. For a computer to see, it must process and analyze images coming from a camera or any input device. Computer vision is most useful in translating gestures, movements, expressions and actions into input commands. Most of the existing motion tracking systems uses the Kalman filter to process moving objects. One downside of the Kalman filter is that it is very slow, and it cannot process objects that move fast and has difficulty isolating random noises from the actual object in motion. Motion trackers that use the condensation algorithm shows satisfactory results, but a lot of improvements are still possible because of the visible problems that arise from its implementation. The system under study, processes images in real-time through a camera and from a saved file in multiple viode format. Moving objects are detected and shown using squares to track its movement. Tracking multiple moving objects is one of the capabilities of the system. It can still track objects in a highly cluttered background where there is a high density of noise present. The aim of this study is to enhance the performance and accuracy of the previous system by improving the algorithm behind the codes. The proponents will try enhance, if not, develop a new algorithm that will comply with what they are trying to pursue.
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