Predictive optical-flow algorithm for aircraft detection

Jeffrey W. McCandless; Albert J. Ahumada Jr.

doi:10.1117/12.325764

6 October 1998 Predictive optical-flow algorithm for aircraft detection

Jeffrey W. McCandless, Albert J. Ahumada Jr.

Proceedings Volume 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision; (1998) https://doi.org/10.1117/12.325764
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States

Abstract

A computer vision algorithm was developed to detect moving aircraft located in video images. Using a gradient-based approach, the algorithm computes optical flow vectors in each frame of the sequence. Vectors with similar characteristics (location, magnitude, and direction) are clustered together using a spatial consistency test. Vectors that pass the spatial consistency test are extended temporally to make predictions about the optical flow locations, magnitudes, and directions in subsequent frames. The actual optical flow vectors that are consistent with the predicted vectors are labeled as vectors associated with a moving target. The algorithm was tested on images obtained with a video camera mounted below the nose of a Boeing 737. The algorithm correctly detected an aircraft from a distance of one mile in over 80% of the frames with zero false alarms.

Citation Download Citation

Jeffrey W. McCandless and Albert J. Ahumada Jr. "Predictive optical-flow algorithm for aircraft detection", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325764

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KEYWORDS

Optical flow

Cameras

Detection and tracking algorithms

Video

Target detection

Algorithm development

Computer vision technology

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