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The micrometeoroid impact hazard in spaceHill, David C. January 1990 (has links)
No description available.
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The 1972 Convention on international liablity for damage caused by space objects /Fenema, H. P. van. January 1973 (has links)
No description available.
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The liability for damage caused by space activities /Saleh, Saleh Tewfik. January 1967 (has links)
No description available.
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The 1972 Convention on international liablity for damage caused by space objects /Fenema, H. P. van. January 1973 (has links)
No description available.
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The liability for damage caused by space activities /Saleh, Saleh Tewfik. January 1967 (has links)
No description available.
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Stability Assessment of Planetary Entry Vehicles in the X3 Superorbital Expansion TubeAbdel-Jawad, M. Unknown Date (has links)
No description available.
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Stability Assessment of Planetary Entry Vehicles in the X3 Superorbital Expansion TubeAbdel-Jawad, M. Unknown Date (has links)
No description available.
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Space law state responsibility for spacecraft damages and for the return of personnel and equipment /Buchmann, Carl E. January 1900 (has links)
Thesis (LL. M.)--Judge Advocate General's School, U.S. Army, 1965. / "1965." Typescript. Includes bibliographical references (leaves 97-105). Also issued in microfiche.
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La réclamation du Canada pour les dommages causés par le satellite soviétique Cosmos 954Farand, André. January 1980 (has links)
No description available.
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Vehicle tracking using scale invariant featuresWang, Jue, Computer Science & Engineering, Faculty of Engineering, UNSW January 2008 (has links)
Object tracking is an active research topic in computer vision and has appli- cation in several areas, such as event detection and robotics. Vehicle tracking is used in Intelligent Transport System (ITS) and surveillance systems. Its re- liability is critical to the overall performance of these systems. Feature-based methods that are used to represent distinctive content in visual frames are one approach to vehicle tracking. Existing feature-based tracking systems can only track vehicles under ideal conditions. They have difficulties when used under a variety of conditions, for example, during both the day and night. They are highly dependent on stable local features that can be tracked for a long time period. These local features are easily lost because of their local property and image noise caused by factors such as, headlight reflections and sun glare. This thesis presents a new approach, addressing the reliability issues mentioned above, tracking whole feature groups composed of feature points extracted with the Scale Invariant Feature Transform (SIFT) algorithm. A feature group in- cludes several features that share a similar property over a time period and can be tracked to the next frame by tracking individual feature points inside it. It is lost only when all of the features in it are lost in the next frame. We cre- ate these feature groups by clustering individual feature points using distance, velocity and acceleration information between two consecutive frames. These feature groups are then hierarchically clustered by their inter-group distance, velocity and acceleration information. Experimental results show that the pro- posed vehicle tracking system can track vehicles with the average accuracy of over 95%, even when the vehicles have complex motions in noisy scenes. It gen- erally works well even in difficult environments, such as for rainy days, windy days, and at night. We are surprised to find that our tracking system locates and tracks motor bikes and pedestrians. This could open up wider opportunities and further investigation and experiments are required to confirm the tracking performance for these objects. Further work is also required to track more com- plex motions, such as rotation and articulated objects with different motions on different parts.
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