Synchrony is observed in countless phenomena and its discovery is central to answering many computer vision and pattern recognition problems. A basic research problem has remained surprisingly underexplored: Given a set of sequences, how can we discover subsets in which every pair of sequences satisfies a synchrony criterion? This problem naturally arises in many domains. For example, in a video, only movement in a subset of pixels is synchronized in time, and their identification can lead to discovering events of interest (e.g., facial expressions).
We develop methods to detect and quantify synchrony in behavioral, biological, and other data types. Our tools can be used in many domains including computer vision, brain connectivity analysis, financial analysis, genetic analysis, among many others.