Abstract: A method of controlling an actuator based on a set of three-dimensional (3D) data points is provided. The method includes obtaining a first set of 3D data points for a scene and a second set of 3D data points for a scene with a sensor. At least a first set of planar features is extracted from the first set of 3D data point. At least a second set of planar features is extracted from the second set of 3D data points. A motion is determined between the first set of 3D data points and the second set of 3D data points based on a rotation and a translation from the at least a first set to the at least a second set. At least one actuator is controlled based on the motion.

Abstract: A new technique for identifying from images a camera, or other imaging device such as a scanner, is based on the device's reference noise pattern, a unique stochastic characteristic of all common digital imaging sensors, including CCD, CMOS (Foveon™ X3), and JFET. First, one determines from images the sensor's reference pattern noise, which uniquely identifies each sensor. To identify the sensor from a given image, the presence or absence of the reference pattern noise in the image under examination is established using a correlation detector or other means.

Abstract: A new technique for identifying whether images are derived from a common imager, e.g., a camera, or other imaging device such as a scanner, based on the device's measured or inferred reference noise pattern, a unique stochastic characteristic of all common digital imaging sensors, including CCD, CMOS (Foveon™ X3), and JFET. The measured or inferred noise pattern of two images may be extracted and then cross correlated, with a high correlation being consistent with a common imager. Various preprocessing techniques may be used to improve tolerance to various types of image transform. It is also possible to perform the analysis without explicit separation of inferred image and inferred noise.

Abstract: A new technique for identifying from images a camera, or other imaging device such as a scanner, is based on the device's reference noise pattern, a unique stochastic characteristic of all common digital imaging sensors, including CCD, CMOS (Foveon™ X3), and JFET. First, one determines from images the sensor's reference pattern noise, which uniquely identifies each sensor. To identify the sensor from a given image, the presence or absence of the reference pattern noise in the image under examination is established using a correlation detector or other means.

Abstract: A new technique for identifying whether images are derived from a common imager, e.g., a camera, or other imaging device such as a scanner, based on the device's measured or inferred reference noise pattern, a unique stochastic characteristic of all common digital imaging sensors, including CCD, CMOS (Foveon™ X3), and JFET. The measured or inferred noise pattern of two images may be extracted and then cross correlated, with a high correlation being consistent with a common imager. Various preprocessing techniques may be used to improve tolerance to various types of image transform. It is also possible to perform the analysis without explicit separation of inferred image and inferred noise.