Transportation prediction system and method

1. An automotive prediction system comprising: a processing circuitry; and a memory to store data used by the processing circuitry, the processing circuitry being configured to:

obtain a plurality of labels labelling a plurality of media content elements identified in a plurality of road-scene media content sequences being at least one of audio or video road-scene sequences, each one label of the plurality of labels including a content descriptor selected from a plurality of different content descriptors describing at least one media content element of the plurality of media content elements, the plurality of different content descriptors including a first content descriptor and a second content descriptor;

calculate a correlation of the first content descriptor and the second content descriptor based on a first count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after, but within a given temporal distance of, the first content descriptor being used for labelling in the plurality of road-scene media content sequences;

calculate a first correlation of the first content descriptor and the second content descriptor based on a second count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after a first temporal distance from the first content descriptor being used for labelling in the plurality of road-scene media content sequences; and

calculate a second correlation of the first content descriptor and the second content descriptor based on a third count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after a second temporal distance from the first content descriptor being used for labelling in the plurality of road-scene media content sequences, the second temporal distance being greater than the first temporal distance; and

populate an automotive prediction database with the correlation of the first content descriptor and the second content descriptor for use in making decisions during driving of a vehicle.

2. The system according to claim 1 , wherein the processing circuitry is further configured to calculate a third correlation of the first content descriptor and the second content descriptor based on a third count of occurrences of the second content descriptor and the first content descriptor being used for labelling in the plurality of road-scene media content sequences at a same temporal location in the plurality of road-scene media content sequences.

3. The system according to claim 1 , wherein each one label of at least some labels from the plurality of labels includes location data indicating a location of one media content element of the plurality of media content elements within a video frame of one road-scene media content sequence of the plurality of road-scene media content sequences, the processing circuitry being further configured to determine a location relationship between the first content descriptor and the second content descriptor based on the location data of the at least some labels.

4. The system according to claim 3 , wherein the processing circuitry is further configured to determine the location relationship including trajectory prediction data of the second content descriptor based on a location or identified trajectory of the first content descriptor.

5. The system according to claim 1 , wherein the processing circuitry is further configured to select the plurality of road-scene media content sequences from a second plurality of media content sequences based on selecting ones of the second plurality of media content sequences that include road-scene content descriptors.

6. The system according to claim 5 , wherein the processing circuitry is further configured to select the plurality of road-scene media content sequences based on a geolocation origin of the second plurality of media content sequences.

7. The system according to claim 1 , wherein the processing circuitry is further configured to improve any one or more of the following: a speed and/or accuracy of calculating the correlation of the first content descriptor and the second content descriptor; an accuracy of predictive correlation data for use in automotive prediction applications to predict a future road-scene event; and an operation speed of a computing device calculating the correlation of the first content descriptor and the second content descriptor.

8. An automotive prediction system comprising: a processing circuitry; and a memory to store data used by the processing circuitry, the processing circuitry being configured to:

obtain a plurality of labels labelling a plurality of media content elements identified in a plurality of road-scene media content sequences being at least one of audio or video road-scene sequences, each one label of the plurality of labels including a content descriptor selected from a plurality of different content descriptors describing at least one media content element of the plurality of media content elements, the plurality of different content descriptors including a first content descriptor and a second content descriptor;

calculate a correlation of the first content descriptor and the second content descriptor based on a first count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after, but within a given temporal distance of, the first content descriptor being used for labelling in the plurality of road-scene media content sequences; and

populate an automotive prediction database with the correlation of the first content descriptor and the second content descriptor for use in making decisions during driving of a vehicle;

determine a first value based on a second count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences;

determine a second value based on the first count of occurrences; and

calculate the correlation of the first content descriptor and the second content descriptor based on the first value and the second value.

9. The system according to claim 8 , wherein the processing circuitry is further configured to determine the second value based on the first count of occurrences divided by a third count of occurrences of the first content descriptor being used for labelling in the plurality of road-scene media content sequences.

10. An automotive prediction system comprising: a processing circuitry; and a memory to store data used by the processing circuitry, the processing circuitry being configured to:

obtain a plurality of labels labelling a plurality of media content elements identified in a plurality of road-scene media content sequences being at least one of audio or video road-scene sequences, each one label of the plurality of labels including a content descriptor selected from a plurality of different content descriptors describing at least one media content element of the plurality of media content elements, the plurality of different content descriptors including a first content descriptor and a second content descriptor;

calculate a correlation of the first content descriptor and the second content descriptor based on a first count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after, but within a given temporal distance of, the first content descriptor being used for labelling in the plurality of road-scene media content sequences; and

populate an automotive prediction database with the correlation of the first content descriptor and the second content descriptor for use in making decisions during driving of a vehicle;

wherein the plurality of content descriptors includes a third content descriptor which is different from the first content descriptor and the second content descriptor; and

the processing circuitry is further configured calculate a correlation of the first content descriptor, the second content descriptor, and the third descriptor based on a second count of occurrences of the third content descriptor being used for labelling in the plurality of road-scene media content sequences after a first temporal distance from the first content descriptor being used for labelling and after a second temporal distance from the second content descriptor being used for labelling in the plurality of road-scene media content sequences.

11. An automotive prediction method, comprising:

obtaining a plurality of labels labelling a plurality of media content elements identified in a plurality of road-scene media content sequences being audio and/or video road-scene sequences, each one label of the plurality of labels including a content descriptor selected from a plurality of different content descriptors describing at least one media content element of the plurality of media content elements, the plurality of different content descriptors including a first content descriptor and a second content descriptor;

calculating a correlation of the first content descriptor and the second content descriptor based on a count of occurrences of the second content descriptor and the first content descriptor being used for labelling within a given temporal distance of each other in the plurality of road-scene media content sequences;

calculating a first correlation of the first content descriptor and the second content descriptor based on a second count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after a first temporal distance from the first content descriptor being used for labelling in the plurality of road-scene media content sequences;

calculating a second correlation of the first content descriptor and the second content descriptor based on a third count of occurrences of the second content descriptor being used for labelling in the plurality of road-scene media content sequences after a second temporal distance from the first content descriptor being used for labelling in the plurality of road-scene media content sequences, the second temporal distance being greater than the first temporal distance; and

populating an automotive prediction database with the correlation of the first content descriptor and the second content descriptor for use in making decisions during driving of a vehicle.

12. The method according to claim 11 , further comprising calculating a third correlation of the first content descriptor and the second content descriptor based on a third count of occurrences of the second content descriptor and the first content descriptor being used for labelling in the plurality of road-scene media content sequences at a same temporal location in the plurality of road-scene media content sequences.