Phased Feature Extraction Network for Vehicle Search Tasks Based on Cross-Camera for Vehicle-Road Collaborative Perception.

The objective of vehicle search is to locate and identify vehicles in uncropped, real-world images, which is the combination of two tasks: vehicle detection and re-identification (Re-ID). As an emerging research topic, vehicle search plays a significant role in the perception of cooperative autonomous vehicles and road driving in the distant future and has become a trend in the future development of intelligent driving. However, there is no suitable dataset for this study.

Affective salience can reverse the effects of stimulus-driven salience on eye movements in complex scenes.

In natural vision both stimulus features and cognitive/affective factors influence an observer's attention. However, the relationship between stimulus-driven ("bottom-up") and cognitive/affective ("top-down") factors remains controversial: Can affective salience counteract strong visual stimulus signals and shift attention allocation irrespective of bottom-up features? Is there any difference between negative and positive scenes in terms of their influence on attention deployment? Here we examined the impact of affective factors on eye movement behavior, to understand the competition between visual stimulus-driven salience and affective salience and how they affect gaze allocation in complex scene viewing. Building on our previous research, we compared predictions generated by a visual salience model with measures indexing participant-identified emotionally meaningful regions of each image.