Texas Instruments Corporation

Michael Peter Lachmayr

Mihir Narendra Mody

Hetul Sanghvi

Anish Reghunath

Niraj Nandan

A computer vision system is provided that includes an image generation device configured to capture consecutive two dimensional (2D) images of a scene, a first memory configured to store the consecutive 2D images, a second memory configured to store a growing window of consecutive rows of a reference image and a growing window of consecutive rows of a current image, wherein the reference image and the current image are a pair of consecutive 2D images stored in the first memory, a third memory configured to store a sliding window of pixels fetched from the growing window of the reference image, wherein the pixels in the sliding window are stored in tiles, and a dense optical flow engine (DOFE) configured to determine a dense optical flow map for the pair of consecutive 2D images, wherein the DOFE uses the sliding window as a search window for pixel correspondence searches.

Hierarchical data organization for dense optical flow processing in a computer vision system

A computer vision system is provided that includes an image generation device configured to generate consecutive two dimensional (2D) images of a scene, and a dense optical flow engine (DOFE) configured to determine a dense optical flow map for pairs of the consecutive 2D images, wherein, for a pair of consecutive 2D images, the DOFE is configured to perform a predictor based correspondence search for each paxel in a current image of the pair of consecutive 2D images, wherein, for an anchor pixel in each paxel, the predictor based correspondence search evaluates a plurality of predictors to select a best matching pixel in a reference image of the pair of consecutive 2D images, and determine optical flow vectors for each pixel in a paxel based on the best matching pixel selected for the anchor pixel of the paxel.

Dense optical flow processing in a computer vision system

Systems and methods for performing Census Transforms that includes an input from an image, with a support window created within the image, and a kernel within the support window. The Census Transform calculations and comparisons are performed within the kernel windows. A new Census Transform is disclosed which always inverts a previously made comparison. This new approach can be demonstrated to be equivalent to, applying the original Census Transform, on a pre-processed input kernel, where the pre-processing step adds a fractional position index to each pixel within the N&#xd7;N kernel. The fractional positional index ensures that no two pixels are equal to one another, and thereby makes the Original Census algorithm on pre-processed kernel same as the new Census algorithm on original kernel. The hardware design for this new Census Transform kernel allows for an always invert of previous comparison system resulting in reduced hardware and power consumption.

System and method for an efficient hardware implementation of census transform

Systems and methods for performing Census Transforms that includes an input from an image, with a support window created within the image, and a kernel within the support window. The Census Transform calculations and comparisons are performed within the kernel windows. One disclosed method allows for previously performed comparison to be calculated and compared as an if not equal invert or if equal use pervious comparison hardware design. Alternatively, a new Census Transform is disclosed which always inverts a previously made comparison. This new approach can be demonstrated to be equivalent to, applying the original Census Transform, on a pre-processed input kernel, where the pre-processing step adds a fractional position index to each pixel within the N&#xd7;N kernel. The fractional positional index ensures that no two pixels are equal to one another, and thereby makes the Original Census algorithm on pre-processed kernel same as the new Census algorithm on original kernel. The hardware design for this new Census Transform kernel allows for an always invert of previous comparison system resulting in reduced hardware and power consumption.

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Boxford, MA, United States of America

Michael Peter Lachmayr