Abstract: A data recommendation method is described. A first label set corresponding to multimedia data can be acquired. At least one second label set each corresponding to one of at least one to-be-recommended data can be acquired. Each second label set can include at least one label each representing a content attribute of the respective to-be-recommended data. A set similarity between the first label set and each of the at least one second label set can be determined according to label positions in the label tree. Target recommendation data matched with the multimedia data can be determined from the to-be-recommended data set according to the set similarity between the first label set and each of the at least one second label set.

Abstract: The present disclosure is applicable to the field of image processing, and provides a portrait deformation method and apparatus. The method includes: reading a picture including a portrait; detecting a facial feature of the portrait in the picture; deforming the detected facial feature according to preset control points, to obtain a corresponding deformation field, the number of the preset control points being greater than 1; and making the deformation field act on the picture, so as to convert the picture into a deformed picture. According to embodiments of the present invention, lines of a deformed portrait are more continuous.

Abstract: The present disclosure is applicable to the field of image processing, and provides a portrait deformation method and apparatus. The method includes: reading a picture including a portrait; detecting a facial feature of the portrait in the picture; deforming the detected facial feature according to preset control points, to obtain a corresponding deformation field, the number of the preset control points being greater than 1; and making the deformation field act on the picture, so as to convert the picture into a deformed picture. According to embodiments of the present invention, lines of a deformed portrait are more continuous.