Abstract: Systems and methods are provided for generating synthetic datasets. The system can generate a plurality of object assets, wherein each asset comprises an object of interest. A plurality of asset classes can be defined, wherein each class comprises a subset of the plurality of assets depicted in a target zone, and wherein each asset of the subset is depicted one or more times in the target zone. The system can determine, for each asset of the plurality of object assets, a representation of a number of times the asset is depicted in an asset class of the plurality of asset classes and determine one or more differences between the representations. At least one random class can be defined, wherein the at least one random class comprises one or more assets of the plurality of object assets to reduce the one or more differences between the representations.

Abstract: Systems and methods are provided for object re-identification. In many scenarios, it would be useful to be able to monitor the movement, actions, etc. of an object, such as a person, moving into and between different camera views of a monitored space. A network of cameras and client edge devices may detect and identify a particular object, and when that object re-appears in another camera view, a comparison can be performed between the data collected regarding the object upon its initial appearance and upon its re-appearance to determine if they are the same object. In this way, data regarding an object can be captured, analyzed, or otherwise processed despite moving from one camera view to another.