A computer-implemented method for determining at least one body measurement of a person, comprising at least the steps of: obtaining a plurality of images of the person, wherein the images in the plurality of images show the person from at least two different angles; selecting at least a sub-set of the received plurality of images to provide first input images; generating segmentation maps for the first input images, wherein the segmentation maps at least distinguish the person from a background; characterized by the steps of: selecting at least a subset of the first input images to provide third input images; determining locations for a number of pre-defined key points (K i) on the human body by inputting the third input images into an artificial neural network configured and trained to infer the location for the key points (K i) based on the input third input images; determining, based on the determined locations for the key points (K i), a subset of the first input images so as to provide fourth input images such that each of the fourth input images corresponds to one view of a set of pre-defined views of the person from different angles (F +, F -, S L, S R); generating, for each of the fourth input images, a silhouette of the person therein by determining an outline of the corresponding segmentation map; and determining (S60; S140) at least one body measurement for the person by inputting the determined locations for the key points (K i) and the generated silhouettes into a body measurement determining model. obtaining a plurality of images of the person, wherein the images in the plurality of images show the person from at least two different angles; selecting at least a sub-set of the received plurality of images to provide first input images; generating segmentation maps for the first input images, wherein the segmentation maps at least distinguish the person from a background; characterized by the steps of: selecting at least a subset of the first input images to provide third input images; determining locations for a number of pre-defined key points (K i) on the human body by inputting the third input images into an artificial neural network configured and trained to infer the location for the key points (K i) based on the input third input images; determining, based on the determined locations for the key points (K i), a subset of the first input images so as to provide fourth input images such that each of the fourth input images corresponds to one view of a set of pre-defined views of the person from different angles (F +, F -, S L, S R); generating, for each of the fourth input images, a silhouette of the person therein by determining an outline of the corresponding segmentation map; and determining (S60; S140) at least one body measurement for the person by inputting the determined locations for the key points (K i) and the generated silhouettes into a body measurement determining model. selecting at least a subset of the first input images to provide third input images; determining locations for a number of pre-defined key points (K i) on the human body by inputting the third input images into an artificial neural network configured and trained to infer the location for the key points (K i) based on the input third input images; determining, based on the determined locations for the key points (K i), a subset of the first input images so as to provide fourth input images such that each of the fourth input images corresponds to one view of a set of pre-defined views of the person from different angles (F +, F -, S L, S R); generating, for each of the fourth input images, a silhouette of the person therein by determining an outline of the corresponding segmentation map; and determining (S60; S140) at least one body measurement for the person by inputting the determined locations for the key points (K i) and the generated silhouettes into a body measurement determining model.