Abstract: Methods and systems for implementing a traditional computer vision algorithm as a neural network. The method includes: receiving a definition of the traditional computer vision algorithm that identifies a sequence of one or more traditional computer vision algorithm operations; mapping each of the one or more traditional computer vision algorithm operations to a set of one or more neural network primitives that is mathematically equivalent to that traditional computer vision algorithm operation; linking the one or more network primitives mapped to each traditional computer vision algorithm operation according to the sequence to form a neural network representing the traditional computer vision algorithm; and configuring hardware logic capable of implementing a neural network to implement the neural network that represents the traditional computer vision algorithm.

Abstract: A pixel filter has a filter module that performs a first recursive filter operation in a first direction through a sequence of pixels to form a first filtered pixel value for each pixel, and performs a second recursive filter operation in a second direction through the sequence of pixels to form a second filtered pixel value for each pixel, the first and second recursive filter operations forming a respective filtered pixel value for a given pixel in dependence on the pixel value at that pixel and the filtered pixel value preceding that pixel in their respective direction of operation. The filtered pixel value of the preceding pixel is scaled by a measure of similarity between data associated with that pixel and its preceding pixel. Filter logic combines the first and second filtered pixel values formed by the first and second recursive filter operations to generate a filter output for the pixel, for each pixel of the sequence.

Abstract: A pixel filter receives a sequence of pixels, each pixel having an associated pixel value. A first recursive filter operation is performed in a first direction through the sequence of pixels to form a first filtered pixel value for each pixel, and a second recursive filter operation is performed in a second direction through the sequence of pixels to form a second filtered pixel value for each pixel. The first and second filtered pixel values for a given pixel are determined in dependence on the pixel value at that pixel and the filtered pixel value preceding that pixel in their respective direction of operation, the filtered pixel value of the preceding pixel being scaled by a measure of similarity between data associated with that pixel and its preceding pixel. For each pixel of the sequence, the first and second filtered pixel values are combined to generate a filter output for the pixel.

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a skin patch identifier configured to identify one or more patches of skin color in a first frame and characterize each patch in the first frame using a respective patch construct of a predefined shape; a first search tile generator configured to generate one or more first search tiles from the one or more patch constructs; and a face detector configured to detect faces in the stream by performing face detection in one or more frames of the stream within the first search tiles.

Abstract: A single-instruction, multiple data processor performs object detection in an image by testing for a plurality of object features in a plurality of image regions, the processor comprising: a set of computation units operable to execute a plurality of classifier sequences in parallel, each classifier sequence comprising a plurality of classifier routines, and each classifier routine comprising identical instructions to the other classifier routines in each of the plurality of classifier sequences; wherein each computation unit is configured to independently maintain data identifying an image region and a feature under test on that computation unit, and each classifier routine is arranged to access the data, test the identified feature against the identified image region and update the data such that the computation units are operable to concurrently test different features against different image regions.

Abstract: A single-instruction, multiple data processor performs object detection in an image by testing for a plurality of object features in a plurality of image regions, the processor comprising: a set of computation units operable to execute a plurality of classifier sequences in parallel, each classifier sequence comprising a plurality of classifier routines, and each classifier routine comprising identical instructions to the other classifier routines in each of the plurality of classifier sequences; wherein each computation unit is configured to independently maintain data identifying an image region and a feature under test on that computation unit, and each classifier routine is arranged to access the data, test the identified feature against the identified image region and update the data such that the computation units are operable to concurrently test different features against different image regions.

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a skin patch identifier configured to identify one or more patches of skin colour in a first frame and characterise each patch in the first frame using a respective patch construct of a predefined shape; a first search tile generator configured to generate one or more first search tiles from the one or more patch constructs; and a face detector configured to detect faces in the stream by performing face detection in one or more frames of the stream within the first search tiles.

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a skin patch identifier configured to identify one or more patches of skin color in a first frame and characterize each patch in the first frame using a respective patch construct of a predefined shape; a first search tile generator configured to generate one or more first search tiles from the one or more patch constructs; and a face detector configured to detect faces in the stream by performing face detection in one or more frames of the stream within the first search tiles.

Abstract: A pixel filter includes an input arranged to receive a sequence of pixels, each pixel having an associated pixel value; a filter module arranged to perform a first recursive filter operation in a first direction through the sequence of pixels so as to form a first filtered pixel value for each pixel, and perform a second recursive filter operation in a second direction through the sequence of pixels so as to form a second filtered pixel value for each pixel, wherein the first and second recursive filter operations form a respective filtered pixel value for a given pixel in dependence on the pixel value at that pixel and the filtered pixel value preceding that pixel in their respective direction of operation, the filtered pixel value of the preceding pixel being scaled by a measure of similarity between data associated with that pixel and its preceding pixel; and filter logic configured to, for each pixel of the sequence, combine the first and second filtered pixel values formed in respect of the pixel by the

Abstract: A single-instruction, multiple data processor performs object detection in an image by testing for a plurality of object features in a plurality of image regions, the processor comprising: a set of computation units operable to execute a plurality of classifier sequences in parallel, each classifier sequence comprising a plurality of classifier routines, and each classifier routine comprising identical instructions to the other classifier routines in each of the plurality of classifier sequences; wherein each computation unit is configured to independently maintain data identifying an image region and a feature under test on that computation unit, and each classifier routine is arranged to access the data, test the identified feature against the identified image region and update the data such that the computation units are operable to concurrently test different features against different image regions.

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a face detector configured to detect a first face candidate in a first frame by performing face detection within first search tiles defined for the first frame; a color measurement unit configured to calculate a set of color parameters including an average color of the first face candidate expressed according to a predefined color space; a transformation unit configured to: transform a second frame into the predefined color space, one of the axes of the color space being substantially oriented in the direction of maximum variation according to a predetermined distribution of skin color; and form a skin color probability map for the second frame by calculating the probability that a given color is a skin color from a measure of the color space distance of that color from the calculated average color; and a search tile generator configured to generate second search tiles based on th

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a face detector configured to detect a first face candidate in a first frame by performing face detection within first search tiles defined for the first frame; a colour measurement unit configured to calculate a set of colour parameters including an average colour of the first face candidate expressed according to a predefined colour space; a transformation unit configured to: transform a second frame into the predefined colour space, one of the axes of the colour space being substantially oriented in the direction of maximum variation according to a predetermined distribution of skin colour; and form a skin colour probability map for the second frame by calculating the probability that a given colour is a skin colour from a measure of the colour space distance of that colour from the calculated average colour; and a search tile generator configured to generate second search tile

Abstract: A data processing system for performing face detection on a stream of frames of image data, the data processing system comprising: a skin patch identifier configured to identify one or more patches of skin colour in a first frame and characterise each patch in the first frame using a respective patch construct of a predefined shape; a first search tile generator configured to generate one or more first search tiles from the one or more patch constructs; and a face detector configured to detect faces in the stream by performing face detection in one or more frames of the stream within the first search tiles.