Panasonic Corporation

Etsuko Nagao, Legal Representative

Kenji Nagao

Taro Imagawa

Masahiro Iwasaki

Mihoko Shimano

A normal line information estimation device for estimating normal line information of an object from an image of the object. The normal line information estimation device includes an illumination direction estimation section for estimating an illumination direction with respect to the object in the image from a luminance value of the image; a normal line information estimation section for estimating the normal line information of the object in the image based on the illumination direction; and a specular reflection component estimation section for estimating a specular reflection component of the image from the normal line information of the object and the illumination direction with respect to the object. The normal line information estimation section estimates the normal line information again from the image from which a specular reflection component has been removed in the specular reflection component section.

Normal line information estimation device, registered image group formation device and image collation device, and normal line information estimation method

A parameter estimation method for estimating a parameter by estimating maximum a posteriori probability for input data. Operation for the input data is expressed by an inner product for the input data and the inner product is replaced by a Kernel function. By using the calculation result of the kernel function, a parameter is estimated. The method includes a step (offline operation) for learning a correlation between a plurality of learning input data in which a parameter to be estimated is known and the parameter corresponding to each of the learning input data; and a step (online operation) for estimating the parameter for the estimating input data in which a parameter to be estimated is unknown, by using the learned correlation.

Parameter estimation method, parameter estimation device and collation method

The present invention provides a human detection device which detects a human contained in a moving picture, and includes the following: a spatiotemporal volume generation unit which generates a three-dimensional spatiotemporal image in which frame images that make up the moving picture in which a human has been filmed are arranged along a temporal axis; a spatiotemporal fragment extraction unit which extracts a real image spatiotemporal fragment, which is an image appearing in a cut plane or cut fragment when the three-dimensional spatiotemporal image is cut, from the generated three-dimensional spatiotemporal image; a human body region movement model spatiotemporal fragment output unit which generates and outputs, based on a human movement model which defines a characteristic of the movement of a human, a human body region movement spatiotemporal fragment, which is a spatiotemporal fragment obtained from a movement by the human movement model; a spatiotemporal fragment verification unit which verifies between a real image spatiotemporal fragment and a human body region movement model spatiotemporal fragment; and an attribute output unit which outputs a human attribute which includes the presence/absence of a human in the moving picture, based on that verification result.

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Kanagawa, Japan

Etsuko Nagao, Legal Representative