A preliminary experiment definition for video landmark acquisition and tracking

Six scientific objectives/experiments were derived which consisted of agriculture/forestry/range resources, land use, geology/mineral resources, water resources, marine resources and environmental surveys. Computer calculations were then made of the spectral radiance signature of each of 25 candidate targets as seen by a satellite sensor system. An imaging system capable of recognizing, acquiring and tracking specific generic type surface features was defined. A preliminary experiment definition and design of a video Landmark Acquisition and Tracking system is given. This device will search a 10-mile swath while orbiting the earth, looking for land/water interfaces such as coastlines and rivers

Investigation of a new method for improving image resolution for camera tracking applications

Camera based systems have been a preferred choice in many motion tracking applications due to the ease of installation and the ability to work in unprepared environments. The concept of these systems is based on extracting image information (colour and shape properties) to detect the object location. However, the resolution of the image and the camera field-of- view (FOV) are two main factors that can restrict the tracking applications for which these systems can be used. Resolution can be addressed partially by using higher resolution cameras but this may not always be possible or cost effective. This research paper investigates a new method utilising averaging of offset images to improve the effective resolution using a standard camera. The initial results show that the minimum detectable position change of a tracked object could be improved by up to 4 times

Experimental and simulation study results for video landmark acquisition and tracking technology

A synopsis of related Earth observation technology is provided and includes surface-feature tracking, generic feature classification and landmark identification, and navigation by multicolor correlation. With the advent of the Space Shuttle era, the NASA role takes on new significance in that one can now conceive of dedicated Earth resources missions. Space Shuttle also provides a unique test bed for evaluating advanced sensor technology like that described in this report. As a result of this type of rationale, the FILE OSTA-1 Shuttle experiment, which grew out of the Video Landmark Acquisition and Tracking (VILAT) activity, was developed and is described in this report along with the relevant tradeoffs. In addition, a synopsis of FILE computer simulation activity is included. This synopsis relates to future required capabilities such as landmark registration, reacquisition, and tracking

A data extraction system for underwater particle holography

Pulsed laser holography is an extremely powerful technique for the study of particle fields as it allows instantaneous, noninvasive high-resolution recording of substantial volumes. By replaying the real image one can obtain the size, shape, position and - if multiple exposures are made - velocity of every object in the recorded field. Manual analysis of large volumes containing thousands of particles is, however, an enormous and time-consuming task, with operator fatigue an unpredictable source of errors. Clearly the value of holographic measurements also depends crucially on the quality of the reconstructed image: not only will poor resolution degrade size and shape measurements, but aberrations such as coma and astigmatism can change the perceived centroid of a particle, affecting position and velocity measurements. For large-scale applications of particle field holography, specifically the in situ recording of marine plankton with 'HoloCam,' we have developed an automated data extraction system that can be readily switched between the in-line and off-axis geometries and provides optimised reconstruction from holograms recorded underwater. As a videocamera is automatically stepped through the 200 by 200 by 1000mm sample volume, image processing and object tracking routines locate and extract particle images for further classification by a separate software module