Texture filtering is applied to a texture represented with a mipmap comprising a plurality of levels, wherein each level of the mipmap comprises an image representing the texture at a respective level of detail. A texture filtering unit has minimum and maximum limits on an amount by which it can alter the level of detail when it filters texels from an image of a single level of the mipmap. The range of level of detail between the minimum and maximum limits defines an intrinsic region of the texture filtering unit. If it is determined that a received input level of detail is in an intrinsic region of the texture filtering unit, texels are read from a single mipmap level of the mipmap, and the read texels from the single mipmap level are filtered to determine a filtered texture value representing part of the texture at the input level of detail. If it is determined that the received input level of detail is in an extrinsic region of the texture filtering unit: texels are read from two mipmap levels of the mipmap, and the read texels from the two mipmap levels are processed to determine a filtered texture value representing part of the texture at the input level of detail.

Texture filtering is applied to a texture represented with a mipmap comprising a plurality of levels, wherein each level of the mipmap comprises an image representing the texture at a respective level of detail. A texture filtering unit has minimum and maximum limits on an amount by which it can alter the level of detail when it filters texels from an image of a single level of the mipmap. The range of level of detail between the minimum and maximum limits defines an intrinsic region of the texture filtering unit. If it is determined that a received input level of detail is in an intrinsic region of the texture filtering unit, texels are read from a single mipmap level of the mipmap, and the read texels from the single mipmap level are filtered to determine a filtered texture value representing part of the texture at the input level of detail. If it is determined that the received input level of detail is in an extrinsic region of the texture filtering unit: texels are read from two mipmap levels of the mipmap, and the read texels from the two mipmap levels are processed to determine a filtered texture value representing part of the texture at the input level of detail.

Provided are systems and methods for personalized videos featuring multiple persons. An example method includes receiving a user selection of a video having at least one frame with metadata that include a first location and a second location and receiving an image of a source face and a further image of a further source face, modifying the image of the source face to generate an image of a modified source face and modifying the further image of the further source face to generate an image of a modified further source face, inserting, in the at least one frame of the video, the image of the modified source face at the first location and the image of the modified further source face at the second location to generate a personalized video, and sending the personalized video via a communication chat.

Provided are systems and methods for personalized videos featuring multiple persons. An example method includes receiving a user selection of a video having at least one frame with metadata that include a first location and a second location and receiving an image of a source face and a further image of a further source face, modifying the image of the source face to generate an image of a modified source face and modifying the further image of the further source face to generate an image of a modified further source face, inserting, in the at least one frame of the video, the image of the modified source face at the first location and the image of the modified further source face at the second location to generate a personalized video, and sending the personalized video via a communication chat.

The invention relates to technologies for visualizing a three-dimensional (3D) image. According to the claimed method, a 3D model is generated, images of an object are produced, a 3D model is visualized, the 3D model together with a reference pattern and also coordinates of texturing portions corresponding to polygons of the 3D model are stored in a depiction device, at least one frame of the image of the object is produced, the object in the frame is identified on the basis of the reference pattern, a matrix of conversion of photo image coordinates into dedicated coordinates is generated, elements of the 3D model are coloured in the colours of the corresponding elements of the image by generating a texture of the image sensing area using the coordinate conversion matrix and data interpolation, with subsequent designation of the texture of the 3D model.

The invention relates to technologies for visualizing a three-dimensional (3D) image. According to the claimed method, a 3D model is generated, images of an object are produced, a 3D model is visualized, the 3D model together with a reference pattern and also coordinates of texturing portions corresponding to polygons of the 3D model are stored in a depiction device, at least one frame of the image of the object is produced, the object in the frame is identified on the basis of the reference pattern, a matrix of conversion of photo image coordinates into dedicated coordinates is generated, elements of the 3D model are coloured in the colours of the corresponding elements of the image by generating a texture of the image sensing area using the coordinate conversion matrix and data interpolation, with subsequent designation of the texture of the 3D model.

A system and method are provided for capturing an image with correct skin tone exposure. In use, one or more faces having threshold skin tone are detected within a scene. Based on the detected one or more faces, a high dynamic range (HDR) capture mode is enabled. Further, the scene image is captured using the HDR capture mode.

A system and method are provided for capturing an image with correct skin tone exposure. In use, one or more faces having threshold skin tone are detected within a scene. Based on the detected one or more faces, a high dynamic range (HDR) capture mode is enabled. Further, the scene image is captured using the HDR capture mode.

An online matching and optimization method combining geometry and texture and a three-dimensional (3D) scanning system are provided. The method includes obtaining pairs of depth texture images with a one-to-one corresponding relationship, and collecting the pairs of the depth texture images including depth images by a depth sensor and collecting texture images by a camera device; adopting a strategy of coarse to fine to perform feature, matching on the depth texture images corresponding to a current frame and on the depth texture images corresponding to the target frames, to estimate a preliminary pose of the depth sensor in the 3D scanning system; combining a geometric constraint and a texture constraint to optimize the estimated preliminary pose, and obtaining a refined motion estimation between the frames.

An online matching and optimization method combining geometry and texture and a three-dimensional (3D) scanning system are provided. The method includes obtaining pairs of depth texture images with a one-to-one corresponding relationship, and collecting the pairs of the depth texture images including depth images by a depth sensor and collecting texture images by a camera device; adopting a strategy of coarse to fine to perform feature, matching on the depth texture images corresponding to a current frame and on the depth texture images corresponding to the target frames, to estimate a preliminary pose of the depth sensor in the 3D scanning system; combining a geometric constraint and a texture constraint to optimize the estimated preliminary pose, and obtaining a refined motion estimation between the frames.