Abstract: A computer implemented method for pose estimation of an image sensor includes receiving an omnidirectional image of a scene captured by an image sensor; using a trained neural network to generate a rotation equivariant feature map from the omnidirectional image of the scene; and determining information relating to the pose of said camera when capturing the scene from the rotation equivariant feature map. The rotation equivariant feature map is a SO(3) indexed feature map.

Abstract: A computer-implemented method for place recognition including: obtaining information identifying an image of a first scene; identifying a plurality of pixel clusters in the image; generating a set of feature vectors associated with the pixel clusters; generating a graph of the scene; adding a first edge between a first node and a second node in response to determining that a first property associated with a first pixel cluster is similar to a second property associated with a second pixel cluster; generating a vector representation of the graph; calculating a measure of similarity between the vector representation of the graph and a reference vector representation associated with a second scene; and determining that the first scene and the second scene are associated with a same place in response to determining that the measure of similarity is less than a threshold.

Abstract: A computer vision method for generating a three dimensional reconstruction of an object, the method comprising: receiving a set of photometric stereo images of the object, the set of photometric stereo images comprising a plurality of images using illumination from different directions using one or more light sources; using a trained neural network to generate a normal map of the object; and producing a 3D reconstruction of said object from said normal map, wherein using said trained neural network comprises converting said set of photometric stereo images to an input form suitable for an input layer of said neural network, wherein said input form comprises, for each pixel, a representation of the different lighting directions and their corresponding intensities which have been obtained from photometric stereo images to which a compensation has been applied, the compensation being determined from an estimate of the distance between the lighting source and a point on the object to which the pixel correspond

Abstract: A method for processing video data comprising a plurality of image frames, the method comprising: obtaining a forward model and a backward model of the plurality of image frames; processing the forward model and the backward model to propagate at least one label in the region or patch to at least one other image frame of the video sequence, using a probabilistic method for estimating the label in the at least one other image frame in forward and backward correspondences, wherein, during the processing, a pixel having a most likely label with a probability lower than a threshold value is assigned a predetermined generic label; and generating a labelled result for any given image frame by applying an image label difference, based on label uncertainty between the forward and backward correspondences, to the given image frame.

Abstract: A computer implemented method for pose estimation of an image sensor, the method comprising: receiving an omnidirectional image of a scene captured by an image sensor; using a trained neural network to generate a rotation equivariant feature map from said omnidirectional image of the scene; and determining information relating to the pose of said camera when capturing the scene from said rotation equivariant feature map, wherein the rotation equivariant feature map is a SO(3) indexed feature map.

Abstract: A computer vision method for generating a three dimensional reconstruction of an object, the method comprising: receiving a set of photometric stereo images of the object, the set of photometric stereo images comprising a plurality of images using illumination from different directions using one or more light sources; using a trained neural network to generate a normal map of the object; and producing a 3D reconstruction of said object from said normal map, wherein using said trained neural network comprises converting said set of photometric stereo images to an input form suitable for an input layer of said neural network, wherein said input form comprises, for each pixel, a representation of the different lighting directions and their corresponding intensities which have been obtained from photometric stereo images to which a compensation has been applied, the compensation being determined from an estimate of the distance between the lighting source and a point on the object to which the pixel correspond

Abstract: A method for processing video data comprising a plurality of image frames, the method comprising: obtaining a forward model and a backward model of the plurality of image frames; processing the forward model and the backward model to propagate at least one label in the region or patch to at least one other image frame of the video sequence, using a probabilistic method for estimating the label in the at least one other image frame in forward and backward correspondences, wherein, during the processing, a pixel having a most likely label with a probability lower than a threshold value is assigned a predetermined generic label; and generating a labelled result for any given image frame by applying an image label difference, based on label uncertainty between the forward and backward correspondences, to the given image frame.

Abstract: Methods and apparatus for triggering directional data capture based on pointing direction are described. In an embodiment, the data captured is an image and a camera is described which includes a sensor for detecting the direction in which the image sensor of the camera is pointing. When the sensed pointing direction is one in which a worthwhile image is likely to be taken, the camera is triggered to capture a new image. The determination of when to capture a new image uses a metric based on the sensed direction and one or more specified trigger conditions.

Abstract: Methods and apparatus for triggering directional data capture based on pointing direction are described. In an embodiment, the data captured is an image and a camera is described which includes a sensor for detecting the direction in which the image sensor of the camera is pointing. When the sensed pointing direction is one in which a worthwhile image is likely to be taken, the camera is triggered to capture a new image. The determination of when to capture a new image uses a metric based on the sensed direction and one or more specified trigger conditions.