Current computational models of visual attention focus on bottom-up information and ignore scene context. However, studies in visual cognition show that humans use context to facilitate object dctectionin natural scenes by directing their anention or eyes to diagnostic regions. Here we propose a model of attention guidance based on global scene configuration. We show that the statistics of low-level features across the scene image determine where a specific object (e.g. a person') should he located. Human eye movements show that regions chosen by the top-down model agree with regions scrutinized by human observers performing a visual search task for people. The results validate the proposition that top-down information from visual context modulates the saliency of image regions during the task of object detection. Contextual information provides a shortcut for efficient object detection systems.
Oliva et al. REF proposed a top-down saliency detection framework based on global scene configuration for object detection.
Top-down control of visual attention in object detection
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)
Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)
Computer Science