Mathematical Problems in Engineering / 2013 / Article / Tab 1

Research Article

Eigen-Gradients for Traffic Sign Recognition

Table 1

General comparison with the methods reported in [2]. In the central column a brief description of the method is given: classification tool, image size, number of attributes per image, and features used for recognition.

Team Method Accuracy

IDSIA [3] CNN + MLP, image size , 8 attributes per pixel (18,432 attributes per image), color features 99.46
INI-RTCV Human performance (best individual) 99.22
INI-RTCV Human performance (average) 98.84
Sermanet [4] CNN, image size , 3,072 attributes per image, color features 98.31
CAOR [5] k-NN + Random Forests, image size , 1,568 attributes per image, HOG 2 features 96.14
INI-RTCV LDA, image size , 1,568 attributes per image, HOG 2 features 95.68
INI-RTCV LDA, image size , 1,568 attributes per image, HOG 1 features 93.18
INI-RTCV LDA, image size , 2,916 attributes per image, HOG 3 features 92.34
Eigen-Gradients MLP, image size , 140 attributes per image, gradient-orientation + PCA features 95.9

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