Abstract: A method of correcting gaze offset in an image of at least one individual having eyes is disclosed. The method comprises: processing the image to extract location of at least one eye over the image, processing the image to replace imagery data associated with each location of each eye with replacement data thereby providing a corrected image, and transmitting the corrected image to a display device. The replacement data are preferably previously-recorded imagery data which respectively correspond to the same eye but a different gaze.

Abstract: A system, computer readable medium and a method for motion detection, the method includes: receiving multiple frames; generating a set of digits for each pixel of multiple pixels of each frame of the multiple frames; wherein each set of digits represents a pixel that belongs to a patch of a frame and represents relationships between (a) first similarities between the patch and a set of patches of a next frame that are located in locations that differ from each other and differ from a location of the patch; and (b) second similarities between the patch and a set of patches of a previous frame that are located in locations that differ from each other and differ from a location of the patch; and processing the sets of digits to detect motion.

Abstract: A method and system for statistical mapping between genetic information and facial image data including collecting a multiplicity of sets of genetic information and matching facial image data representing a multiplicity of individuals, representing the genetic information of each of the multiplicity of individuals as a first multidimensional representation, representing the facial image data of each of the multiplicity of individuals as a second multidimensional representation; and inferring correlative, non-causal, statistical relationships between the first multidimensional representations and the second multidimensional representations.

Abstract: A method for providing an output image, the method includes: determining an importance value for each input pixels out of multiple input pixels of an input image; applying on each of the multiple input pixels a conversion process that is responsive to the importance value of the input pixel to provide multiple output pixels that form the output image; wherein the input image differs from the output image.

Abstract: An artificial visual recognition system and method employ a digital processor and a model executed by the digital processor. The model has a loose hierarchy of layers. Each layer, from a lowest hierarchy level to a top level, provides relatively increasing selectivity and invariance of the input image. The hierarchy allows bypass routes between layers. On output, the model produces feature recognition and classification of an object in the input image. In some embodiments, windowing means provide windows of the input image to the model, and the model responds to shape-based objects in the input image. In another feature, segmenting means segment the input image and enables the model to determine texture-based objects in the input image.

Abstract: An artificial visual recognition system and method employ a digital processor and a model executed by the digital processor. The model has a loose hierarchy of layers. Each layer, from a lowest hierarchy level to a top level, provides relatively increasing selectivity and invariance of the input image. The hierarchy allows bypass routes between layers. On output, the model produces feature recognition and classification of an object in the input image. In some embodiments, windowing means provide windows of the input image to the model, and the model responds to shape-based objects in the input image. In another feature, segmenting means segment the input image and enables the model to determine texture-based objects in the input image.