Abstract: The disclosed method generates a pose invariant feature by normalizing off-angle faces to generate a pose invariant input image. Any face recognition mode can be used with this pre processing step. In this method, method, the 3D Spatial Transformer Networks is used to extract a 3D model of the face from an input at any pose.

Abstract: The present invention provides a novel approach to simultaneously extracting the 3D shape of the face and the semantically consistent 2D alignment using a 3D Spatial Transformer Network (3DSTN) to model both the camera projection matrix and the warping parameters of a 3D model. By utilizing a generic 3D model and a thin plate spline (TPS) warping function, subject-specific 3D shapes are able to be generated without the need for a large 3D shape basis.

Abstract: The present invention provides a novel approach to simultaneously extracting the 3D shape of the face and the semantically consistent 2D alignment using a 3D Spatial Transformer Network (3DSTN) to model both the camera projection matrix and the warping parameters of a 3D model. By utilizing a generic 3D model and a thin plate spline (TPS) warping function, subject-specific 3D shapes are able to be generated without the need for a large 3D shape basis.

Abstract: A camera and method identify moving objects of interest in a field of view of the camera. The method includes: capturing two or more images successively over a time period, each image being associated with different times during the time period; obtaining binary image from each successive pair of images, the binary image comprising a binary value at each pixel indicating whether a change in pixel values of at least a predetermined magnitude has occurred at that pixel between the time associated with the first image of the success pair of images and time associated with the second image of the successive pair of images; deriving one or more motion boxes each encapsulating one or more nearby pixels in binary image; processing motion boxes of each binary image to obtain refined motion boxes; and classifying refined motion boxes each into categories representative of one moving object of interest.

Abstract: A camera and method identify moving objects of interest in a field of view of the camera. The method includes: capturing two or more images successively over a time period, each image being associated with different times during the time period; obtaining binary image from each successive pair of images, the binary image comprising a binary value at each pixel indicating whether a change in pixel values of at least a predetermined magnitude has occurred at that pixel between the time associated with the First image of the success pair of images and time associated with the second image of the successive pair of images; deriving one or more motion boxes each encapsulating one or more nearby pixels in binary image; processing motion boxes of each binary image to obtain refined motion boxes; and classifying refined motion boxes each into categories representative of one moving object of interest.