Abstract: The present disclosure is directed to systems and methods for context-aware and personalized access to data corresponding to an event. The data is related to multiple predefined parameters including a location, date, time, and a classifier representing a status or an impact intensity for the event. The method includes receiving the data and an event type for the data. The event type is selected from multiple predefined event types. The method also includes creating a hierarchical data structure configured to spatially index the data based on the selected event type. The hierarchical data structure includes a node representing the selected event type. The node is augmented using a linked list for referring to the data to be stored in a database. The node is associated with a frequency of occurrence of the selected event type.

Abstract: A method, non-transitory computer readable medium and apparatus for detecting a window in a display are disclosed. For example, the method includes scanning pixels within each frame of a plurality of frames that is displayed via a sliding window, extracting one or more features from each pixel within the sliding window, applying a classification function to classify a subset of potential pixels comprising the each pixel within the sliding window as corner pixels based on the one or more features that match predefined features associated with the corner pixels and detecting the window based on the corner pixels and additional pixels within a boundary defined by the corner pixels.