A phase deviation method determines an offset between a reference and suspect signal by analyzing a phase deviation surface created by computing a deviation metric for phase shift and then analyzing a surface formed from the deviation metrics for an array of offsets. The phase deviation method analyzes the deviation surface to determine an offset that minimizes phase deviation. This method is applied at increasing levels of detail to refine the determination of the offset.

In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

The invention relates to a labeling apparatus (1) for labeling structures of an object shown in an object image. A probability map providing unit (3) provides a probability map, the probability map indicating for different labels, which are indicative of different structures of the object, and for different positions in the probability map the probability that the respective structure, which is indicated by the respective label, is present at the respective position, wherein the probability depends on the position in the probability map. The probability map is mapped to the object image by a mapping unit (4), wherein a label assigning unit (5) assigns to a provided contour, which represents a structure in the object image, a label based on the mapped probability map. This allows automatically labeling structures of the object, which are indicated by provided contours in the object image, with relatively low computational efforts.

A method for identifying authenticity of an object, the method includes maintaining, in an identification server system, a reference image of an original object, the reference image and provided to represent all equivalent original objects, receiving, in the identification server system, one or more input images of the object to be identified, and generating, by the identification server system, a target image from the one or more input images. The method further includes aligning, by the identification server system, the target image with the reference image and analysing, by the identification server system, the target image in relation to the aligned reference image for identifying authenticity of the object.

In some implementations, a computer-implemented method for recognizing facial images may include a multi-stage facial verification process to improve the speed and accuracy of a facial recognition operation. For example, a facial recognition module may include multiple stages where a subset of data is analyzed recursively to improve the speed of the facial recognition processes. The multiple stages may be arranged in a fast-to-slow and coarse-to-fine arrangements such that a match decision may be made at each successive stage.

A phase deviation method determines an offset between a reference and suspect signal by analyzing a phase deviation surface created by computing a deviation metric for phase shift and then analyzing a surface formed from the deviation metrics for an array of offsets. The phase deviation method analyzes the deviation surface to determine an offset that minimizes phase deviation. This method is applied at increasing levels of detail to refine the determination of the offset.

A system and method that includes training a classifier using uniquely defined landmark points along the windshield region based on an elastic deformation model. The deformation model uses mixtures of trees with a shared pool of parts and can be globally optimized with dynamic programming and still capture much relevant global elastic structure. Once a candidate area is identified in the scene, a learned threshold is applied to the classification score of the candidate area to determine if the candidate area is a windshield. The identified area is then cropped out for further downstream process.

A method for face alignment operates on a face image and a set of intitial landmark locations by first aligning globally the initial locations to a set of landmark locations of a face with a prototype shape to obtain global alignment parameters, and then warping the initial locations and the image from a coordinate frame of the image to a coordinate frame of the prototype shape according to the global alignment parameters to obtain warped landmark locations and a warped face image. Features are extracted from the warped face image at the warped landmark locations, and a regression function is applied to the features to obtain updated landmark locations in the coordinate frame of the prototype shape. Finally, the updated landmark locations in the coordinate frame of the prototype shape are warped to the coordinate frame of the image, to obtain updated landmark locations.

A system, a method, and a non-transitory computer readable recording medium for recognizing a passenger vehicle make and model are disclosed, which includes a make and model recognition (MMR) database, which is constructed from rear view videos of passenger vehicles.