There is provided a system configured to receive a plurality of images, analyze a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors based on one or more of individual attributes and a second training performance of a plurality of joint detectors based on one or more of composite attributes, select, based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying a plurality of objects in the plurality of images, and identify the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.
BACKGROUND(1) Conventional object recognition schemes enable identification of objects in images based on image attributes and object attributes. Computer vision may be trained to identify parts of an image using independent attributes, such as a noun describing an object or an adjective describing the object, or using composite attributes, such as describing an object using a noun describing the object and an adjective describing the object. However, the conventional schemes do not offer an effective method for identifying some objects. Even more, the conventional schemes are computationally expensive and prohibitively inefficient.SUMMARY(2) The present disclosure is directed to systems and methods for identifying objects in media contents, such as images and video contents, substantially as shown in and/or described in connection with at least one of the figures, as set forth more completely in the claims.
1. A system comprising: a non-transitory memory storing an attribute database including individual attributes and composite attributes, each of the composite attributes including two or more of the individual attributes; and a hardware processor executing an executable code to: receive a plurality of images; analyze a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors and a second training performance of a plurality of joint detectors, wherein the plurality of independent detectors are for identifying a plurality of objects in the plurality of images based on one or more of the individual attributes, and wherein the plurality of joint detectors are for identifying the plurality of objects in the plurality of images based on one or more of the composite attributes; select, based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying the plurality of objects in the plurality of images; and identify the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.
6. A method for use with a system including a hardware processor and a non-transitory memory storing an attribute database including individual attributes and composite attributes, each of the composite attributes including two or more of the individual attributes, the method comprising: receiving, using the hardware processor, a plurality of images; analyzing, using the hardware processor, a set of features of the plurality of images to determine a difference between a first training performance of a plurality of independent detectors and a second training performance of a plurality of joint detectors, wherein the plurality of independent detectors are for identifying a plurality of objects in the plurality of images based on one or more of the individual attributes, and wherein the plurality of joint detectors are for identifying the plurality of objects in the plurality of images based on one or more of the composite attributes; selecting, using the hardware processor and based on the analyzing, either one of the plurality of independent detectors or one of the plurality of joint detectors for identifying the plurality of objects in the plurality of images; and identifying the plurality of objects in the plurality of images, using the selected one of the plurality of independent detectors utilizing the one or more of the individual attributes or using the selected one of the plurality of joint detectors utilizing the one or more of the composite attributes.