Abstract: An approach is provided for generating synthetic image data for machine learning. The approach, for instance, involves determining, by a processor, a set of parameters for indicating an action by one or more objects. The action is a dynamic movement of the one or more objects through a geographic space over a period of time. The approach also involves processing the set of parameters to generate synthetic image data. The synthetic image data includes a computer-generated image sequence of the one or more objects performing the action in the geographic space over the period of time. The approach further involves automatically labeling the synthetic image data with at least one label representing the action, the set of parameters, or a combination thereof. The approach further involves providing the labeled synthetic image data for training or evaluating a machine learning model to detect the action.

Abstract: An approach is provided for generating synthetic image data for machine learning. The approach, for instance, involves determining, by a processor, a set of parameters for indicating an action by one or more objects. The action is a dynamic movement of the one or more objects through a geographic space over a period of time. The approach also involves processing the set of parameters to generate synthetic image data. The synthetic image data includes a computer-generated image sequence of the one or more objects performing the action in the geographic space over the period of time. The approach further involves automatically labeling the synthetic image data with at least one label representing the action, the set of parameters, or a combination thereof. The approach further involves providing the labeled synthetic image data for training or evaluating a machine learning model to detect the action.

Abstract: An approach is provided for generating synthetic image data for machine learning. The approach, for instance, involves determining, by a processor, a set of parameters for indicating an action by one or more objects. The action is a dynamic movement of the one or more objects through a geographic space over a period of time. The approach also involves processing the set of parameters to generate synthetic image data. The synthetic image data includes a computer-generated image sequence of the one or more objects performing the action in the geographic space over the period of time. The approach further involves automatically labeling the synthetic image data with at least one label representing the action, the set of parameters, or a combination thereof. The approach further involves providing the labeled synthetic image data for training or evaluating a machine learning model to detect the action.

Abstract: An approach is provided for generating synthetic image data for machine learning. The approach, for instance, involves determining, by a processor, a set of parameters for indicating an action by one or more objects. The action is a dynamic movement of the one or more objects through a geographic space over a period of time. The approach also involves processing the set of parameters to generate synthetic image data. The synthetic image data includes a computer-generated image sequence of the one or more objects performing the action in the geographic space over the period of time. The approach further involves automatically labeling the synthetic image data with at least one label representing the action, the set of parameters, or a combination thereof. The approach further involves providing the labeled synthetic image data for training or evaluating a machine learning model to detect the action.