Abstract: An apparatus including a processor and memory having computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: use a classification model to identify one or more anomalies between a monitored trajectory of a vehicle through a road network and predefined map data for the road network which are likely caused by errors in the predefined map data; and provide details of the one or more identified anomalies for use in obtaining additional data for the specific locations on the road network corresponding to the one or more identified anomalies in order to correct the errors in the predefined map data.

Abstract: Methods are provided for modeling mobility based on one or more devices of the user. Methods may include: receiving at least a portion of a first mobility model from a first device, where the first mobility model may be established based on learning algorithms performed on the first device; updating a shared mobility model to become a first shared mobility model based on the at least a portion of the first mobility model; providing the first shared mobility model to the first device; receiving at least a portion of a second mobility model from a second device, where the second mobility model may be established based on learning algorithms performed on the second device; updating the first shared mobility model to become a second shared mobility model based on the at least a portion of the second mobility model; and providing the second shared mobility model to the second device.

Abstract: An apparatus comprising a processor and memory including computer program code, the memory and computer program code configured to, with the processor, enable the apparatus at least to: use a classification model to identify one or more anomalies between a monitored trajectory of a vehicle through a road network and predefined map data for the road network which are likely caused by errors in the predefined map data; and provide details of the one or more identified anomalies for use in obtaining additional data for the specific locations on the road network corresponding to the one or more identified anomalies in order to correct the errors in the predefined map data.

Abstract: Methods are provided for modeling mobility based on one or more devices of the user. Methods may include: receiving at least a portion of a first mobility model from a first device, where the first mobility model may be established based on learning algorithms performed on the first device; updating a shared mobility model to become a first shared mobility model based on the at least a portion of the first mobility model; providing the first shared mobility model to the first device; receiving at least a portion of a second mobility model from a second device, where the second mobility model may be established based on learning algorithms performed on the second device; updating the first shared mobility model to become a second shared mobility model based on the at least a portion of the second mobility model; and providing the second shared mobility model to the second device.

Abstract: A method and apparatus for object based motion compensation forms objects from blocks of an input image based on motion similarity of the blocks in the input image and a reference image. In addition, object motion compensation vectors for each formed object and object relative block motion compensation vectors for each object's constituent blocks relative to the object's motion compensation vector are computed.

Abstract: A method and apparatus for object based motion compensation forms objects from blocks of an input image based on motion similarity of the blocks in the input image and a reference image. In addition, object motion compensation vectors for each formed object and object relative block motion compensation vectors for each object's constituent blocks relative to the object's motion compensation vector are computed.