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H. Eidenberger, M. Hörhan:
"An Efficient DCT template-based Object Detection Method using Phase Correlation";
Vortrag: Asilomar Conference on Signals, Systems, and Computers, Pacific Grove; 06.11.2016 - 09.11.2016; in: "Asilomar Conference on Signals, Systems, and Computers Proceedings MA8b3-4", MA8b3-4 (2016).

In this work, we propose an efficient algorithm,
which utilizes the combination of discrete cosine transform (DCT)
and phase correlation (PC) for fast object detection. To test the
algorithm´s classification performance and computational
complexity we developed a prototype and conducted several
experiments with a public available car dataset. Furthermore, we
compared our experimental results to a state-of-the-art object
detection method. The proposed method uses the energy
compaction property of DCT and requires less number of
coefficients than fast Fourier transformation (FFT)-based
techniques to compute PC. The computational complexity and
memory requirements are significantly reduced using this method.
According to our results, the proposed algorithm outperforms the
baseline method with respect to training time and classification
accuracy.

In this work, we propose an efficient algorithm,
which utilizes the combination of discrete cosine transform (DCT)
and phase correlation (PC) for fast object detection. To test the
algorithm´s classification performance and computational
complexity we developed a prototype and conducted several
experiments with a public available car dataset. Furthermore, we
compared our experimental results to a state-of-the-art object
detection method. The proposed method uses the energy
compaction property of DCT and requires less number of
coefficients than fast Fourier transformation (FFT)-based
techniques to compute PC. The computational complexity and
memory requirements are significantly reduced using this method.
According to our results, the proposed algorithm outperforms the
baseline method with respect to training time and classification
accuracy.