Cognitech, Inc.

Other

Leonid I Rudin

Ping Yu

Jose Luis Lisani

Pascal Monasse

Jean-Michel Morel

Pablo Musé

Jean Michel Morel

Frederic Guichard

Stanley Osher

Frédéric Cao

Jose-Luis Lisani

Determining GPS coordinates of some image point(s) positions in at least two images using a processor configured by program instructions. Receiving position information of some of the positions where an image capture device captured an image. Determining geometry by triangulating various registration objects in the images. Determining GPS coordinates of the image point(s) positions in at least one of the images. Saving GPS coordinates to memory. This system and method may be used to determine GPS coordinates of objects in an image.

System and method for determining geo-location(s) in images

Detecting a pattern in an image by receiving the image of a pattern and storing the image in a memory, where the pattern is composed of shapes that have geometrical properties that are invariant under near projective transforms. In some embodiments the process detects shapes in the image using the geometrical properties of the shapes, determines the alignment of the various shapes, and, corresponds or matches the shapes in the image with the shapes in the pattern. This pattern detection process may be used for calibration or distortion correction in optical devices.

System and method for pattern detection and camera calibration

Information of different scans of physical objects may require comparison, for example to determine if the scans are of the same object or if an object has changed, or better information for a three dimensional model may be desired. Different scans of physical objects may be compared by determining lines or planes tangent to a surface at a discrete number of points, registering three dimensional information provided by the scans using the tangent lines or planes, and determining a measure of discrepancy between the surfaces. Three dimensional information of different scans of the same object may also be merged after determining lines or planes tangent to a surface at a discrete number of points and performing registration and merging.

Registration and comparison of three-dimensional objects

Lossless video data compression is performed in real time at the data rate of incoming real time video data in a process employing a minimum number of computational steps for each video pixel. Each pixel 8-bit byte is converted to a difference byte representing the difference between the pixel and its immediate predecessor in a serialized stream of the pixel bytes. This reduces the dynamic range of the data. Any carry bits generated in the subtraction process of two's complement arithmetic are discarded. This reduces the data by a factor of two. Finally, the 8-bit difference pixel bytes thus produced are subject to a maximum entropy encoding process. Such a maximum entropy encoding process may be referred to as a minimum length encoding process.

Lossless video data compressor with very high data rate

An image analysis technology that enables real-time fully 3-dimensionally integrated reconstruction of the live video-data derived from CCTV system's multiple camera observations of a spatially connected surveillance scene.

Real-time 3-D video-security

Indexing regions of changed pixels (ROCHs) in a collection of images by receiving a collection of images. Estimate and/or validate a background among the collection of images. Detect the changes between images in the collection. Associate the detected changes between the images and classifying the associated changes. This image processing method and system may be used for image indexing and object classification.

System and method for image and video search, indexing and object classification

Registration and comparison of three dimensional objects in facial imaging

Lossless video data compression is performed in real time at the data rate of incoming real time video data in a process employing a minimum number of computational steps for each video pixel. A first step is to convert each pixel 8-bit byte to a difference byte representing the difference between the pixel and its immediate predecessor in a serialized stream of the pixel bytes. Thus, each 8-bit pixel byte is subtracted from its predecessor. This step reduces the dynamic range of the data. A next step is to discard any carry bits generated in the subtraction process of two's complement arithmetic. This reduces the data by a factor of two. Finally, the 8-bit difference pixel bytes thus produced are subject to a maximum entropy encoding process. Such a maximum entropy encoding process may be referred to as a minimum length encoding process. One example is Huffman encoding. In such an encoding process, a code table for the entire video frame is constructed, in which a set of minimum length symbols are correlated to the set of difference pixel bytes comprising the video frame, the more frequently occurring bytes being assigned to the shorter minimum length symbols. This code table is then employed to convert the all of the difference pixel bytes of the entire video frame to minimum length symbols.

Methods and systems for grouping video frames. The video frames may be from a multiplexed stream of video frames from a plurality of video sources. In some embodiments video frames are grouped by determining if the video frames share meaningful modes for values representative of features of the video frames.

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San Marino, CA, United States of America

Leonid I Rudin