An incident handler receives a plurality of incident reports, each incident report characterizing an incident occurring within a geographical area. An incident model generator generates an incident model, based on, for each incident, an occurrence time window and an occurrence area within the geographical area. An incident estimator receives a new incident report characterizing a new incident occurring within the geographical area and recorded within a plurality of media files captured by at least one media capture device, the new incident report including a new occurrence time window and new occurrence area. The incident estimator further prioritizes the plurality of media files, based on the incident model, the new occurrence time window, and the new occurrence area, in an order corresponding to a likelihood of inclusion of the new incident therein. A media manager selects and sorts the prioritized media files for ordered playback thereof.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed, are configured to cause at least one processor to: receive a plurality of incident reports, each incident report characterizing an incident occurring within a geographical area; generate an incident model, based on, for each incident, an occurrence time window and an occurrence area within the geographical area; receive a new incident report characterizing a new incident occurring within the geographical area and recorded within a plurality of media files captured by at least one media capture device; and prioritize the plurality of media files, based on the incident model, in an order corresponding to a likelihood of inclusion of the new incident therein. 2. The computer program product of claim 1, wherein the instructions, when executed, are configured to cause the at least one processor to: receive, categorize, and store the plurality of incident reports according to an associated incident type for each incident report. 3. The computer program product of claim 1, wherein the occurrence time window is defined as existing between a time from which a corresponding incident first may have happened, and a time at which the incident was ascertained to have actually happened. 4. The computer program product of claim 3, wherein, in the incident model, occurrence time windows for each historical incident are divided into time segments, and a weight is assigned to each time segment based on its inclusion in one or more of the occurrence time windows. 5. The computer program product of claim 1, wherein the occurrence area is defined as a portion of the geographic area including a route over which a moving object moved to travel from a start point to an end point of the occurrence area. 6. The computer program product of claim 5, wherein, in the incident model, occurrence areas for each historical incident are divided into geo-intervals, and a weight is assigned to each geo-interval based on its inclusion in one or more of the occurrence areas. 7. The computer program product of claim 6, wherein the occurrence area includes a route along one or more streets, and the geo-intervals include street segments of the one or more streets. 8. The computer program product of claim 1, wherein the instructions, when executed, are configured to cause the at least one processor to: retrieve the incident model from among a plurality of incident models, based on a new occurrence time of the new incident and on a new occurrence area for the new incident. 9. The computer program product of claim 8, wherein the instructions, when executed, are configured to cause the at least one processor to: retrieve the incident model based on a correspondence of incident type between a type of the incident model and a type of the new incident. 10. The computer program product of claim 1, wherein the instructions, when executed, are configured to cause the at least one processor to: update the incident model based on the new incident, including adding a new occurrence time window and new occurrence area; and select incident reports from the incident model, based on the new occurrence time window and the new occurrence area. 11. The computer program product of claim 10, wherein the instructions, when executed, are configured to cause the at least one processor to: divide the new occurrence time window into time segments and assign a weight to each time segment based on its inclusion in one or more of the occurrence time windows and the new occurrence time window; divide the new occurrence are into geo-intervals and assign a weight to each geo-interval based on its inclusion in one or more of the occurrence areas and the new occurrence areas. 12. The computer program product of claim 11, wherein the instructions, when executed, are configured to cause the at least one processor to: assign probabilities to each of the time segments, based on the weight assigned to each time segment; assign probabilities to each of the geo intervals, based on the weight assigned to each geo-interval. 13. The computer program product of claim 12, wherein the instructions, when executed, are configured to cause the at least one processor to: combine the probabilities assigned to each of the geo intervals with the probabilities assigned to each of the time segments to thereby obtain probabilities that the new incident was recorded at corresponding times and geo-intervals by the at least one media capture device; and prioritize the plurality of media files, based on the combined probabilities. 14. A computer-implemented method for executing instructions stored on a non-transitory computer readable storage medium, the method comprising: receiving a plurality of incident reports, each incident report characterizing an incident occurring within a geographical area; generating an incident model, based on, for each incident, an occurrence time window and an occurrence area within the geographical area, wherein the occurrence time window is defined as existing between a time from which a corresponding incident first may have happened, and a time at which the incident was ascertained to have actually happened, and wherein the occurrence area is defined as a portion of the geographic area including a route over which a moving object moved to travel from a start point to an end point of the occurrence area; receiving a new incident report characterizing a new incident occurring within the geographical area and recorded within a plurality of media files captured by at least one media capture device, the new incident report including a new occurrence time window and new occurrence area; and prioritizing the plurality of media files, based on the incident model, the new occurrence time window, and the new occurrence area, in an order corresponding to a likelihood of inclusion of the new incident therein. 15. The method of claim 14, wherein, in the incident model, occurrence time windows for each historical incident are divided into time segments, and a weight is assigned to each time segment based on its inclusion in one or more of the occurrence time windows, and in the incident model, occurrence areas for each historical incident are divided into geo-intervals, and a weight is assigned to each geo-interval based on its inclusion in one or more of the occurrence areas. 16. The method of claim 14, comprising: dividing the new occurrence time window into time segments; assigning a weight to each time segment based on its inclusion in one or more of the occurrence time windows and the new occurrence time window; dividing the new occurrence area into geo-intervals; and assigning a weight to each geo-interval based on its inclusion in one or more of the occurrence areas and the new occurrence areas. 17. The method of claim 16, comprising: assigning probabilities to each of the time segments, based on the weight assigned to each time segment; assigning probabilities to each of the geo intervals, based on the weight assigned to each geo-interval; combining the probabilities assigned to each of the geo intervals with the probabilities assigned to each of the time segments to thereby obtain probabilities that the new incident was recorded at corresponding times and geo-intervals by the at least one media capture device; and prioritizing the plurality of media files, based on the combined probabilities. 18. A system comprising: at least one processor; and instructions recorded on a non-transitory computer-readable medium, and executable by the at least one processor, the system including an incident handler configured to cause the at least one processor to receive a plurality of incident reports, each incident report characterizing an incident occurring within a geographical area; an incident model generator configured to cause the at least one processor to generate an incident model, based on, for each incident, an occurrence time window and an occurrence area within the geographical area; an incident estimator configured to cause the at least one processor to receive a new incident report characterizing a new incident occurring within the geographical area and recorded within a plurality of media files captured by at least one media capture device, the new incident report including a new occurrence time window and new occurrence area, and further configured to cause the at least one processor to prioritize the plurality of media files, based on the incident model, the new occurrence time window, and the new occurrence area, in an order corresponding to a likelihood of inclusion of the new incident therein; and a media manager configured to cause the at least one processor to select and sort the prioritized media files for ordered playback thereof. 19. The system of claim 18, wherein the incident estimator is further configured to cause the at least one processor to: divide the new occurrence time window into time segments; assign a weight to each time segment based on its inclusion in one or more of the occurrence time windows and the new occurrence time window; divide the new occurrence area into geo-intervals; and assign a weight to each geo-interval based on its inclusion in one or more of the occurrence areas and the new occurrence areas. 20. The system of claim 18, wherein the incident estimator is further configured to cause the at least one processor to: assign probabilities to each of the time segments, based on the weight assigned to each time segment; assign probabilities to each of the geo intervals, based on the weight assigned to each geo-interval; combine the probabilities assigned to each of the geo intervals with the probabilities assigned to each of the time segments to thereby obtain probabilities that the new incident was recorded at corresponding times and geo-intervals by the at least one media capture device; and prioritize the plurality of media files, based on the combined probabilities.