Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for automated identification and tagging of video content. Example methods may include determining a first set of frames in video content, determining a first set of faces that appear in the first set of frames, and extracting first image content corresponding to respective faces of the first set of faces. Methods may include classifying the first image content into a first set of clusters, generating a second set of clusters comprising a second set of faces, wherein the second set of faces has less faces than the first set of faces, and determining a first actor identifier associated with a first face in the second set of clusters. Some methods may include determining second image content in the second set of clusters comprising the first face, and automatically associating the first actor identifier with the second image content.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.

Abstract: A flight ticket transfer system obtains an identification of a traveler and of an earlier booked flight, provides a listing of earlier departing flights, receives a selection of an earlier departing flight from among the listing of the earlier departing flights, identifies an earlier departing booked airline corresponding to the earlier departing booked flight, and sends to the earlier departing booked airline a flight luggage request, receives from a transfer feasibility module a success response to the luggage request, relative to an estimated time for transfer of the traveler's luggage from the earlier booked flight to the selected earlier departing flight, and completes a purchase of a ticket for the selected earlier departing flight.

Abstract: Methods, systems, and computer program products for pre-cooling and pre-heating vehicles using crowd estimation techniques are provided herein. A computer-implemented method includes estimating the number of individuals having travelled in a vehicle over sub-routes of a fixed route, learning temporal patterns pertaining to the number of individuals in the vehicle across each of the sub-routes, predicting the number of individuals that will be in the vehicle during the sub-routes based on the patterns, computing an expected amount of time for the vehicle to complete a sub-route and arrive at a location that commences a subsequent sub-route, determining an amount by which the energy required to maintain a temperature range in the vehicle is to be modified prior to the vehicle reaching the location based on said predicting and said computing, and utilizing energy to maintain the temperature range, based on said determining, prior to the vehicle reaching the location.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.

Abstract: Methods, systems, and computer program products for pre-cooling and pre-heating vehicles using crowd estimation techniques are provided herein. A computer-implemented method includes estimating the number of individuals having travelled in a vehicle over sub-routes of a fixed route, learning temporal patterns pertaining to the number of individuals in the vehicle across each of the sub-routes, predicting the number of individuals that will be in the vehicle during the sub-routes based on the patterns, computing an expected amount of time for the vehicle to complete a sub-route and arrive at a location that commences a subsequent sub-route, determining an amount by which the energy required to maintain a temperature range in the vehicle is to be modified prior to the vehicle reaching the location based on said predicting and said computing, and utilizing energy to maintain the temperature range, based on said determining, prior to the vehicle reaching the location.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.

Abstract: A venue occupant comfort system, comprises a processor that stores computer executable components stored in memory. A plurality of sensors sense ambient conditions associated with exterior and interior conditions of a venue. A context component infers or determines context of an occupant of the venue. A crowd estimation component infers, based at least in part on mining social networks, size of crowd expected at the venue. A comfort model component implicitly and explicitly trained on occupant comfort related data analyzes information from the plurality of sensors, the crowd estimation component and context component. A comfort controller adjusts environmental conditions of the venue based at least in part on output of the comfort model component. The adjustments to venue environment can optionally be differentiated by zone.