A ground truth engine comprising: a memory holding a plurality of captured images depicting an articulated item; a processor configured to access a parameterized, three dimensional, 3D, model of the item; an optimizer configured to compute ground truth values of the parameters of the 3D model for individual ones of the captured images by computing, using an energy function expressing how the 3D model is expected to fit the captured energy, an optimization comprising an iterative process, such that the articulated item depicted in the captured image fits the 3D model, the optimizer configured to take into account feedback data from one or more humans, about accuracy of a plurality of the computed values of the parameters, and characterized in that: the optimizer is configured to take into account the feedback data by: converting the feedback data into a form suitable for aggregation, wherein the optimizer is configured to receive the feedback data in form of annotations on a 3D view of the 3D model, the annotations comprising labels of one or more joints or parts of the articulated item and at least one penalty function, wherein the penalty function comprises a feedback accuracy range within which the penalty function has no influence on the energy function, and wherein the penalty function is a quartic function clamped at zero during the accuracy range; and forming an optimized energy function by aggregating the at least one penalty function with the energy function; and wherein: the optimizer is configured such that after use of the optimized energy function, the optimizer re-runs using the energy function without the penalty function. a memory holding a plurality of captured images depicting an articulated item; a processor configured to access a parameterized, three dimensional, 3D, model of the item; an optimizer configured to compute ground truth values of the parameters of the 3D model for individual ones of the captured images by computing, using an energy function expressing how the 3D model is expected to fit the captured energy, an optimization comprising an iterative process, such that the articulated item depicted in the captured image fits the 3D model, the optimizer configured to take into account feedback data from one or more humans, about accuracy of a plurality of the computed values of the parameters, and characterized in that: the optimizer is configured to take into account the feedback data by: converting the feedback data into a form suitable for aggregation, wherein the optimizer is configured to receive the feedback data in form of annotations on a 3D view of the 3D model, the annotations comprising labels of one or more joints or parts of the articulated item and at least one penalty function, wherein the penalty function comprises a feedback accuracy range within which the penalty function has no influence on the energy function, and wherein the penalty function is a quartic function clamped at zero during the accuracy range; and forming an optimized energy function by aggregating the at least one penalty function with the energy function; and wherein: the optimizer is configured such that after use of the optimized energy function, the optimizer re-runs using the energy function without the penalty function. the optimizer is configured to take into account the feedback data by: converting the feedback data into a form suitable for aggregation, wherein the optimizer is configured to receive the feedback data in form of annotations on a 3D view of the 3D model, the annotations comprising labels of one or more joints or parts of the articulated item and at least one penalty function, wherein the penalty function comprises a feedback accuracy range within which the penalty function has no influence on the energy function, and wherein the penalty function is a quartic function clamped at zero during the accuracy range; and forming an optimized energy function by aggregating the at least one penalty function with the energy function; and wherein: the optimizer is configured such that after use of the optimized energy function, the optimizer re-runs using the energy function without the penalty function.