Panasonic Corporation

Panasonic Intellectual Property Corporation of America

Fumi Kawai

Hiroaki Yoshio

Takayuki Matsukawa

Keisuke Hayata

Katsunori Waragai

Heng Cher Keng

A feature amount calculation apparatus calculates a feature amount of a target object from image data, and is provided with: a feature value calculator that calculates an edge direction and edge magnitude as input image data pixel-unit feature values; a feature amount calculator that has an edge direction group calculator that calculates a group of edge directions, and a correlation value calculator that takes all pixels or predetermined pixels among a plurality of pixels used in feature value calculation as pixels subject to correlation value calculation and calculates an edge magnitude correlation value between the pixels subject to correlation value calculation for each feature value; and a histogram creator that counts feature amounts in a histogram for each correlation value, and creates a histogram as a feature vector.

Feature-amount calculation apparatus, feature-amount calculation method, and program

An object detecting apparatus capable of suppressing an increase of processing loads with high accuracy and a learning apparatus for the same are provided. An object detecting apparatus includes an image window extracting portion () for extracting an image window as a partial area of an image in plural from an input image, and a network identifier () for detecting a presence of an object from extracted image windows respectively by using a node network in which nodes each having an identifier for identifying the object stored in a storing portion () are connected as a network.

Object detecting apparatus and learning apparatus for the same

A multimedia data recording apparatus is disclosed that enables large-volume recorded data to be recorded for a long period in accordance with the importance of the data, by means of a simple configuration and simple processing, and without imposing a heavy load on the system. In this apparatus, a layer classification section classifies video data captured by a surveillance camera and input via a video processing section into a plurality of layers on a frame-by-frame basis according to importance. A data recording section assigns a file to each layer and records classified data in a data recording medium. If an information amount reduction section detects that the vacant capacity of the data recording medium has reached or fallen below a threshold value, it deletes a frame belonging to the lowest layer among the plurality of layers.

Growing community of inventors

Tokyo, Japan

Fumi Kawai