Paper
3 November 2016 A fast pyramid matching algorithm for infrared object detection based on region covariance descriptor
Li-hua Yin, Xiao Wang, Jiang-rong Xie
Author Affiliations +
Abstract
In order to achieve the purpose of infrared object detection, two phases are essential, including feature selection and matching strategy. Good Features should be discriminative, robust and easy to compute. The matching strategy affects the accuracy and efficiency of matching. In the first stage, instead of the joint distribution of the image statistics, we use region covariance descriptor and calculate region covariance using integral images. The idea presented here is more general than the image sums or histograms, which were already published before. In the second feature matching stage, we describe a new and fast pyramid matching algorithm under the distance metric, which performed extremely rapidly than a brute force search. We represent an object with five covariance matrices of the image features computed inside the object region. Instead of brute force matching, we constructed the image pyramid and decomposed the source image and object image into several levels, which included different image resolutions. After the completion of coarse match, fine-match is essential. The performance of region covariance descriptor is superior to other methods, and the pyramid matching algorithm performs extremely rapidly and accurately, as it is shown, and the large rotations and illumination changes are also absorbed by the covariance matrix.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Li-hua Yin, Xiao Wang, and Jiang-rong Xie "A fast pyramid matching algorithm for infrared object detection based on region covariance descriptor", Proc. SPIE 10030, Infrared, Millimeter-Wave, and Terahertz Technologies IV, 100301Z (3 November 2016); https://doi.org/10.1117/12.2245977
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KEYWORDS
Infrared radiation

Detection and tracking algorithms

Matrices

Infrared imaging

Infrared detectors

Image resolution

Feature extraction

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