Automated video logging methods and systems
Exemplary embodiments of systems and methods are provided for automatically creating time-based video metadata for a video source and a video playback mechanism. An automated logging process can be provided for receiving a digital video stream, analyzing one or more frames of the digital video stream, extracting a time from each of the one or more frames analyzed, and creating a clock index file associating a time with each of the one or more analyzed frames. The process can further provide for parsing one or more received data files, extracting time-based metadata from the one or more parsed data files, and determining a frame of the digital video stream that correlates to the extracted time based metadata.
1. A system that is adapted to create a clock index; the system comprising:
a logging client, operatively coupling to a network wherein the logging client receives a video frame from the network and the network receives the video frame from a video server;
a data server, communicatively coupled to the logging client through the network;
data files, stored in the data server, and further comprising external metadata;
wherein the logging client is programmed with instructions to:
analyze the video frame with the logging client;
extract a time value from the video frame analyzed;
receive a time-based metadata from the data files;
associate a time with an assigned identifier value for the video frame and the time-based metadata in a database connected to the logging client;
associate external metadata within the data files with the time value;
index the time-based metadata with the assigned identifier value.
2. The process of claim 1 , further comprising searching content of the video frame to produce internal metadata.
3. The process of claim 2 , wherein searching the video frame for the internal metadata includes recognizing faces of individuals on the video frame.
4. The process of claim 2 , wherein searching the video frame for the internal metadata includes extracting text as the internal metadata.
5. The process of claim 2 , wherein searching the video frame for the internal metadata includes extracting graphics as the internal metadata.
6. The process of claim 2 , wherein searching the video frame for the internal metadata includes extracting audio data as the internal metadata.
7. The process of claim 2 , wherein searching the video frame for the internal metadata includes extracting the locations of people depicted in the video as the internal metadata.
8. The process of claim 2 , wherein searching the video frame for the internal metadata includes extracting the relative locations of objects depicted in the video as the internal metadata.
9. The process of claim 8 , further comprising extracting the relative position of people in the video to a fixed object.
10. The process of claim 9 , wherein the fixed object is a basketball court.
11. The process of claim 2 , wherein the internal metadata is at least one subtitle.
12. The process of claim 1 , wherein the video frame is obtained from a live stream.
13. The process of claim 1 , wherein extracting the time from the video frame analyzed further comprises searching the video frame.
14. The process of claim 13 , wherein searching the video frame further comprises automatically detecting coordinates of a clock on each video frame analyzed to extract the time from each video frame using optical character recognition.
15. The process of claim 1 , wherein the logging client pulls the time-based metadata from a data server through a query.
16. The process of claim 1 , wherein the logging client pulls the time-based metadata from a data server through an application programming interface.
17. The process of claim 1 , wherein the data files are obtained from a sensor.