Current video-surveillance systems in urban scenarios are very limited and only consist in a presentation of the visual information captured by the visual sensors network, not oriented to end-users, that limiting thus the capacity to help and prevent the criminal activity. Furthermore, the visual-surveillance systems usually do not have any automatic process to store the more relevant evidences to be used in the legal punitive process of the criminals.
SmartPrevent proposes to address this challenge by:
- Studying the characteristics of frequent criminal activities in real urban scenarios including typical variations and unanticipated criminal situations.
- Developing a low-cost adaptative video-surveillance system in order to detect and prevent criminal activities.
- Building a video-surveillance system as punitive tool in order to store the most relevant evidences of the detected criminal activities.