Video understanding is concerned with the parsing of the image data flow for the semantic understanding of the objects in the scene, but also their actions and interactions defining their behavior. When the objects of interest are people, there is the need to detect them (Tu et al., 2008), recognize them (Wu et al., 2008), but also to track their position, and re-identify them when they reappear (Doretto et al., 2011). By detecting people actions and interactions (Motiian et al., 2017) we can also attempt to predict their future behavior and intent. These techniques can be used to respond to queries that require mining a large corpus of video data for safety and security applications. On the other hand, variations of these techniques could be used to analyze and quantify the behavior of a heart in an echocardiogram.
- TCSVTOnline Human Interaction Detection and Recognition with Multiple Cameras IEEE Transactions on Circuits and Systems for Video Technology, 2017.
- JAIHCAppearance-based person reidentification in camera networks: problem overview and current approaches Journal of Ambient Intelligence and Humanized Computing, 2011.
- ECCVUnified crowd segmentation In Proceedings of European Conference on Computer Vision, 2008.
- CVPRFace alignment using boosted ranking models In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2008. Oral