A computer implemented method of locating fingernails of a person's hand in an image, comprising the steps of: a) storing respective individual representations of at least a plurality of each digit of a person's hand, each individual representation including data defining: a respective digit-shape model and a corresponding function that approximates variations to the digit-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; and a fingernail sub-shape model comprising a subset of the data defining the respective digit-shape model, and a corresponding function that approximates variations to the fingernail sub-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; b) storing a global representation of the plurality of digits of the person's hand, including data defining a global model defining a non-overlapping arrangement of said digit-shape models, and a corresponding function that approximates variations to the global model; c) determining (S4-3 to S4-17) an approximate position of each identified fingernail in the image using an image-based feature detection function; d) determining (S4-23 to S4-33) an approximate position of each digit in the image, based on the global representation and the approximate position of each identified fingernail; e) refining (S4-35; S8-3) the approximate position of each digit in the image, based on the respective digit-shape model and its corresponding function; and f) refining (S4-35; S8-13) the position of each fingernail in the image, based on the respective fingernail sub-shape model and its corresponding function. a) storing respective individual representations of at least a plurality of each digit of a person's hand, each individual representation including data defining: a respective digit-shape model and a corresponding function that approximates variations to the digit-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; and a fingernail sub-shape model comprising a subset of the data defining the respective digit-shape model, and a corresponding function that approximates variations to the fingernail sub-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; a respective digit-shape model and a corresponding function that approximates variations to the digit-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; and a fingernail sub-shape model comprising a subset of the data defining the respective digit-shape model, and a corresponding function that approximates variations to the fingernail sub-shape model, the corresponding function comprising regression coefficient matrices that define an approximation of a trained function that is applied to bring features of a candidate object shape from respective estimated locations to determined positions in an input image; b) storing a global representation of the plurality of digits of the person's hand, including data defining a global model defining a non-overlapping arrangement of said digit-shape models, and a corresponding function that approximates variations to the global model; c) determining (S4-3 to S4-17) an approximate position of each identified fingernail in the image using an image-based feature detection function; d) determining (S4-23 to S4-33) an approximate position of each digit in the image, based on the global representation and the approximate position of each identified fingernail; e) refining (S4-35; S8-3) the approximate position of each digit in the image, based on the respective digit-shape model and its corresponding function; and f) refining (S4-35; S8-13) the position of each fingernail in the image, based on the respective fingernail sub-shape model and its corresponding function.