Human Visual Attention Map for Compressed Video

In this paper, a new implementation of the human attention map is introduced. Most conventional approaches share characteristics such as the pooling rule is fixed and prior knowledge of camera aim is discarded. Unlike previous research, the proposed method allows more freedom at the feature integration stage since human eyes have a different sensitivity for each feature under different video aiming scenarios. An intelligent mechanism is designed to identify the importance of each feature for each type of camera motion and skin tone feature, and the feature integration is adaptive to different content. With this framework, more important features are emphasized and less important features are suppressed