8 accepted papers
Methods based on independent component analysis (ICA) and canonical correlation analysis (CCA) as well as their various extensions have become popular for the fusion of multimodal data as they minimize assumptions about the relationships among multiple datasets. Two important extensions that are wid…
Dynamic functional connectivity has become a prominent approach for tracking the changes of macroscale statistical dependencies between regions in the brain. Effective parametrization of these statistical dependencies, referred to as brain states, is however still an open problem. We investigate dif…
Due to the potential for object occlusion in crowded areas, the use of multiple cameras for video surveillance has prevailed over the use of a single camera. This has motivated the development of a number of techniques to analyze such multi-camera video sequences. However, most of these techniques r…
Independent component analysis (ICA) is a powerful method for blind source separation based on the assumption that sources are statistically independent. Though ICA has proven useful and has been employed in many applications, complete statistical independence can be too restrictive an assumption in…
The existence of complementary information across multiple sensors has driven the proliferation of multivariate datasets. Exploitation of this common information, while minimizing the assumptions imposed on the data has led to the popularity of data-driven methods. Independent vector analysis (IVA),…
The use of in vivo calcium imaging has granted researchers the unprecedented ability to study large populations of neurons in real time, enabling direct observation of how the brain processes information. Such data offers great potential, however for current analysis techniques, successful extractio…
Exploitation of complementary information is the principal reason for collecting data from multiple neurological sensors. Since little is known about the latent processes underlying neural function, it is important to minimize the assumptions placed on the data when performing a joint analysis. This…
Automated detection of abandoned object (AO) is an important application in video surveillance for security purposes. Because of its importance, a number of techniques have been proposed to automatically detect abandoned objects in the past years. However, these techniques require prior knowledge on…