A method for assessing change in an object, the method being performed by an image analysis computing device, and comprising: retrieving, based on a captured version of an object in a received image, one or more training images which display one or more related versions of the object and one or more items of data related to the one or more related versions of the object of the one or more training images; determining one or more keypoints which are invariant to changes in scale and rotation in the captured version of the object in the received image and in the related versions of the object in the one or more training images; identifying one or more changes to the object in the received image based on any of the determined one or more keypoints in the captured version of the object in the received image which do not match one or more keypoints in the related versions of the object in the one or more training images; and providing, to a user, the identified one or more changes in the captured version of the object in the received image, characterized in that the one or more changes to the object are identified by: determining in the captured version of the object in the received image a cluster associated with each of the one or more keypoints in the captured version of the object in the received image which do not match one or more keypoints in the related versions of the object in the one or more training images; identifying one or more parts of the object associated with the unmatched keypoints in the captured version of the object in the received image based on the identified clusters; comparing the one or more identified parts of the captured version of the object in the received image with one or more corresponding parts in the related versions of the object in the one or more training images; and identifying the one or more changes to the object based on the comparison. retrieving, based on a captured version of an object in a received image, one or more training images which display one or more related versions of the object and one or more items of data related to the one or more related versions of the object of the one or more training images; determining one or more keypoints which are invariant to changes in scale and rotation in the captured version of the object in the received image and in the related versions of the object in the one or more training images; identifying one or more changes to the object in the received image based on any of the determined one or more keypoints in the captured version of the object in the received image which do not match one or more keypoints in the related versions of the object in the one or more training images; and providing, to a user, the identified one or more changes in the captured version of the object in the received image, characterized in that the one or more changes to the object are identified by: determining in the captured version of the object in the received image a cluster associated with each of the one or more keypoints in the captured version of the object in the received image which do not match one or more keypoints in the related versions of the object in the one or more training images; identifying one or more parts of the object associated with the unmatched keypoints in the captured version of the object in the received image based on the identified clusters; comparing the one or more identified parts of the captured version of the object in the received image with one or more corresponding parts in the related versions of the object in the one or more training images; and identifying the one or more changes to the object based on the comparison. determining in the captured version of the object in the received image a cluster associated with each of the one or more keypoints in the captured version of the object in the received image which do not match one or more keypoints in the related versions of the object in the one or more training images; identifying one or more parts of the object associated with the unmatched keypoints in the captured version of the object in the received image based on the identified clusters; comparing the one or more identified parts of the captured version of the object in the received image with one or more corresponding parts in the related versions of the object in the one or more training images; and identifying the one or more changes to the object based on the comparison.