Abstract: System for automatically generating AR landmarks for guiding a novice user while performing maintenance operations in a device, such as a mechanical or electronic device. The system comprises one or more video cameras are used to acquire video segments of a sequence of maintenance phases, a computer (with a least one processor) that runs an operation software, for training a Machine Learning (ML) model to identify and classify predetermined parts of the device, tools for performing the maintenance operations by manipulating the state of the parts, manual operations (such as hand gestures) of a professional worker, while using the tools, during manipulation according to a workflow being a sequence of phases for carrying out the maintenance operations. Each phase is a predetermined plurality of corresponding operations performed by the professional worker in any order, to be completed before moving to the next phase.

Abstract: A system and methods are provided for determining an embedding region in a video stream, including: generating a mask of an initial estimate of an embedding region in a video frame of the video stream, wherein an initial boundary is a boundary of the initial estimate of the embedding region; determining a refined boundary as a region demarked by four best line segments; transforming a replacement image to fit the dimensions of the refined boundary; and inserting the transformed replacement image into the video frame, within the refined boundary.

Abstract: Method for online character recognition of Arabic text, the method including receiving handwritten Arabic text from a user in the form of handwriting strokes, sampling the handwriting strokes to acquire a sequence of two dimensional point representations thereof, with associated temporal data, geometrically pre processing and extracting features on the point representations, detecting delayed strokes and word parts in the pre processed point representations, projecting the delayed strokes onto the body of the word parts, constructing feature vector representations for each word part, thereby generating an observation sequence, and determining the word with maximum probability given the observation sequence, resulting in a list of word probabilities.

Abstract: Method for online character recognition of Arabic text, the method including receiving handwritten Arabic text from a user in the form of handwriting strokes, sampling the handwriting strokes to acquire a sequence of two dimensional point representations thereof, with associated temporal data, geometrically pre processing and extracting features on the point representations, detecting delayed strokes and word parts in the pre processed point representations, projecting the delayed strokes onto the body of the word parts, constructing feature vector representations for each word part, thereby generating an observation sequence, and determining the word with maximum probability given the observation sequence, resulting in a list of word probabilities.

Abstract: An occlusion culling method for image processing and system therefor. The culling method first determines which polygons are hidden, or occluded, by other objects. These hidden or occluded polygons will not contribute to the final scene and, therefore, need not be rendered. In the first major step, the input models are preprocessed to build a hierarchical data structure which is as an approximation to the input models. Simple polygonal occluders are determined for substitution in place of the complex image geometry in successive visibility queries. Once the first preprocessing step is complete, the second step may be executed at run-time, while a user is inspecting, or visualizing, the input. In the second step, the occluders, determined in the first step, are used to selectively forego rendering shapes or shape portions that are unseen from the current viewpoint.