Object detection is one of the most challenging issues for computer vision researchers. The analysis of thehuman visual attention mechanisms can help automatic inspection systems, in order to discard useless informationand improving performances and efficiency. In this paper we proposed our attention based method toestimate firearms position in images of people holding firearms. Both top-down and bottom-up mechanismsare 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.
|Titolo della pubblicazione ospite||SIGMAP 2014 - International Conference on Signal Processing and Multimedia Applications|
|Numero di pagine||8|
|Stato di pubblicazione||Published - 2014|
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Graphics and Computer-Aided Design
La Cascia, M., Ardizzone, E., Mazzola, G., & Gallea, R. (2014). Combining Top-down and Bottom-up Visual Saliency for Firearms Localization. In SIGMAP 2014 - International Conference on Signal Processing and Multimedia Applications (pagg. 25-32)