Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network

Figure 5

Features. A sample image (bottom right) and 35 of the features that we use to train the model. These include subband features, Itti and Koch saliency channels, three simple saliency models described by Torralba and GBVS and AWS, color features and automatic horizon, car, people, and face detectors. The labels for our training on this image are based on a threshold saliency map derived from human fixations (to the left of bottom right).