Samsung Electronics Co., Ltd.

Beijing Samsung Telecom R&d Center

Xiangsheng Huang

Dong Soo Kim

Seong-deok Lee

Kyung Shik Roh

Jungbae Kim

Young Bo Shim

Hwa Sup Lim

Won Jun Hwang

Haibing Ren

Jongha Lee

An image processing apparatus and method may accurately separate only humans among moving objects, and also accurately separate even humans who have no motion via human segmentation using a depth data and face detection technology. The apparatus includes a face detecting unit to detect a human face in an input color image, a background model producing/updating unit to produce a background model using a depth data of an input first frame and face detection results, a candidate region extracting unit to produce a candidate region as a human body region by comparing the background model with a depth data of an input second or subsequent frame, and to extract a final candidate region by removing a region containing a moving object other than a human from the candidate region, and a human body region extracting unit to extract the human body region from the candidate region.

Image processing apparatus and image processing method

Disclosed is a 3D face capturing apparatus, method and computer-readable medium. As an example, the 3D face capturing method includes obtaining a face color image, obtaining a face depth image, aligning, by a computer, the face color image and the face depth image, obtaining, by the computer, a 3D face model by 2D modeling of the face color image and covering a modeled 2D face area on an image output by an image alignment module, removing by the computer, depth noise of the 3D face model, and obtaining, by the computer, an accurate 3D face model by aligning the 3D face model and a 3D face template, and removing residual noise based on a registration between the 3D face model and the 3D face template.

Three-dimensional face capturing apparatus and method and computer-readable medium thereof

A multi-view face recognition method and system are provided. In the multi-view face recognition method, two images to be recognized are input, a linear projection matrix is calculated based on grouped images in a training set, two feature vectors corresponding to the two input images are extracted based on the linear projection matrix, a distance between the two extracted feature vectors is calculated, and it is determined based on the distance between the two feature vectors whether the two input images belong to a same person.

Multi-view face recognition method and system

Growing community of inventors

Beijing, China

Xiangsheng Huang