Hybrid multitarget tracking system

Aswinikumar Subramanian; Laurence G. Hassebrook; Sugata Ghosal; Michael Kim

doi:10.1117/12.138166

25 November 1992 Hybrid multitarget tracking system

Aswinikumar Subramanian, Laurence G. Hassebrook, Sugata Ghosal, Michael Kim

Proceedings Volume 1697, Acquisition, Tracking, and Pointing VI; (1992) https://doi.org/10.1117/12.138166
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

A common function for human being is to detect the movement of an object against a stationary background and then to lock on to and trace its motion. This natural process becomes very tedious in industrial or military environments where the database of images to be searched is huge or where the function is to be repeated continuously. Thus automation can assist people carrying out such tasks. This is the case in security systems, military reconnaissance, military targeting, aircraft tracking, assembly line manufacturing systems, and quality control. We present a hybrid system to do such tasks. The technique is simulated on computer using numerical algorithms and is successful under many situations. For implementation an ideal system using optical components is presented. This hybrid system employs three main subsystems which are combined in such a way as to compensate for each other's drawbacks yet enhance each other's virtues. The first system is a velocity correlation system which correlates two adjacent frames in a sequence of image frames. The resultant velocity correlations are searched to find the potential velocity profiles at which an object may be moving. These velocity profiles are then processed by the multi-frame mean subsystem which performs a geometric (or arithmetic mean) operation on the image frames. These frames are displaced by the selected velocity profiles and thereby aligning the object in the given frames for detection. Algorithms have been developed and tested to perform this technique on selected databases. Also algorithms to synthesize test images have been developed and the results are presented.

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Aswinikumar Subramanian, Laurence G. Hassebrook, Sugata Ghosal, and Michael Kim "Hybrid multitarget tracking system", Proc. SPIE 1697, Acquisition, Tracking, and Pointing VI, (25 November 1992); https://doi.org/10.1117/12.138166

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KEYWORDS

Algorithm development

Quantization

Image processing

Databases

Computer simulations

Control systems

Detection and tracking algorithms

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