6533b7d0fe1ef96bd125b8b9
RESEARCH PRODUCT
Combining Top-down and Bottom-up Visual Saliency for Firearms Localization
Giuseppe MazzolaMarco La CasciaEdoardo ArdizzoneRoberto Galleasubject
Firearms Detection Visual Saliency Probabilistic Model.Computer sciencebusiness.industryStatistical modelTop-down and bottom-up designObject detectionPosition (vector)Face (geometry)Visual attentionComputer visionArtificial intelligencebusinessVisual saliencydescription
Object detection is one of the most challenging issues for computer vision researchers. The analysis of the human visual attention mechanisms can help automatic inspection systems, in order to discard useless information and improving performances and efficiency. In this paper we proposed our attention based method to estimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanisms are involved in our system. The bottom-up analysis is based on a state-of-the-art approach. The top-down analysis is based on the construction of a probabilistic model of the firearms position with respect to the people’s face position. This model has been created by analyzing information from of a public available database of movie frames representing actors holding firearms.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-08-01 | Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications |