Abstract: Systems and methods for emotion-based real-time personalization of augmented reality environments are disclosed. Exemplary implementations may: receive a series of original images of a user's face; detect, in the series of images, at least one emotion of the user; modify the series of images in response to the detected emotion(s); and display the modified images on a screen of the personal electronic device. In some embodiments, images may be modified based on one or more detected demographic characteristics of a user. In various implementations, processing may be done locally on a personal electronic device and the modified images displayed substantially in real-time.

Abstract: A system includes at least one camera capable of acquiring at least one first image comprising a representation of at least a portion of a face and at least one processor. The processor is configured to: detect a plurality of landmarks in the at least one first image, the plurality of landmarks corresponding to respective features of the face; detect an emotion expressed in the face; generate a three-dimensional model of the face based, at least in part, on the plurality of detected landmarks; and, in response to a request to incorporate at least one object, generate at least one second image comprising a representation of at least a portion of the at least one object atop of the representation of at least a portion of the face generated from the three-dimensional model, wherein the emotion detected in the face is expressed in the at least one object.

Abstract: A two-dimensional image is transformed into at least one portion of a human or animal body into a three-dimensional model. An image is acquired that includes the at least one portion of the human or animal body. An identification is made of the at least one portion within the image. Searches are made for features indicative of the at least one portion of the human or animal body within the at least one portion. One or more identifications are made of a set of landmarks corresponding to the features. An alignment is a deformable mask including the set of landmarks. The deformable mask includes a number of meshes corresponding to the at least one portion of the human or animal body. The 3D model is animated by dividing it into concentric rings, quasi rings and applying different degrees of rotation to each ring.

Abstract: A two-dimensional image is transformed into at least one portion of a human or animal body into a three-dimensional model. An image is acquired that includes the at least one portion of the human or animal body. An identification is made of the at least one portion within the image. Searches are made for features indicative of the at least one portion of the human or animal body within the at least one portion. One or more identifications are made of a set of landmarks corresponding to the features. An alignment is a deformable mask including the set of landmarks. The deformable mask includes a number of meshes corresponding to the at least one portion of the human or animal body. The 3D model is animated by dividing it into concentric rings, quasi rings and applying different degrees of rotation to each ring.

Abstract: A method is provided for transforming a two-dimensional image of at least one portion of a human or animal body into a three-dimensional model. A search is made of features indicative of at least a portion of the human or animal body within the at least one portion. A set of landmarks is identified that corresponds to the features. A 3D deformable mask is aligned, including the set of landmarks to create a 3D model of the face respecting its morphology, the deformable mask including a number of mesh shapes that correspond to at least one portion of the human or animal. The 3D model is animated by dividing it into concentric rings or quasi rings and applying different degrees of rotation to each ring, or quasi ring.