Intel Corporation

Beijing Smartchip Microelectronics Technology Comp

Xiaobo Hu

Yimin Zhang

Fei Duan

Haibing Ren

Liang Liu

Zhe Zhang

Xiaoke Tang

Jie Gan

Dongyan Zhao

Yanyan Yu

Shiping Zang

Yinzi Tu

Techniques are provided for estimation of human orientation and facial pose, in images that include depth information. A methodology embodying the techniques includes detecting a human in an image generated by a depth camera and estimating an orientation category associated with the detected human. The estimation is based on application of a random forest classifier, with leaf node template matching, to the image. The orientation category defines a range of angular offsets relative to an angle corresponding to the human facing the depth camera. The method also includes performing a three dimensional (3D) facial pose estimation of the detected human, based on detected facial landmarks, in response to a determination that the estimated orientation category includes the angle corresponding to the human facing the depth camera.

Estimation of human orientation in images using depth information from a depth camera

Disclosed are an elliptic curve point multiplication operation method and apparatus. The elliptic curve point multiplication operation method comprises ordered point multiplication and point addition operations. In a point addition operation process, when scanning that a current bit of a scalar K is not 0, a true point addition operation is executed, and when scanning that the current bit of the scalar K is 0, an equivalent point conversion operation is executed; the result of the true point addition operation and the result of the equivalent point conversion operation are stored in an identical register file, the register file comprising multiple registers. According to the elliptic curve point multiplication operation method and apparatus, side channel analysis and security error attack can be effectively resisted.

Elliptic curve point multiplication operation method and apparatus

Systems, apparatuses and methods may generate a map of a search environment based on a probability of a target human being present within the search environment, capture a red, green, blue, depth (RGBD) image of one or more potential target humans in the search environment based on the map, and cause a robot apparatus to obtain a frontal view position with respect to at least one of the one or more potential target humans based on the RGBD images.

Human search and identification in complex scenarios

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Beijing, China

Xiaobo Hu