Canon Kabushiki Kaisha

Kenji Tsukamoto

Masakazu Matsugu

Atsushi Nogami

Kan Torii

Yuki Saito

Yasuo Katano

Hiromi Shiozaki

Mahoro Anabuki

Kaname Tomite

Takayuki Iwamoto

An object detection method includes an image acquisition step of acquiring an image including a target object, a layer image generation step of generating a plurality of layer images by one or both of enlarging and reducing the image at a plurality of different scales, a first detection step of detecting a region of at least a part of the target object as a first detected region from each of the layer images, a selection step of selecting at least one of the layer images based on the detected first detected region and learning data learned in advance, a second detection step of detecting a region of at least a part of the target object in the selected layer image as a second detected region, and an integration step of integrating a detection result detected in the first detection step and a detection result detected in the second detection step.

Object detection method, object detection apparatus, and program

The present invention aims to estimate a more consistent posture in regard to a multi-joint object. A target range image is first input, a human body region is extracted from the input range image, a target joint position candidate is calculated from the input range image, and a joint position is finally determined based on the calculated joint position candidate and a likelihood of each joint to estimate the posture. At this time, joint position permissible range information concerning inter-joint distance and angle of a human body model previously set by learning is obtained from a human body model storing unit, consistency is evaluated for a relation between the joint position candidates of a certain joint and other joint based on the obtained information, and thus the posture corresponding to the best combination of the joint positions is determined.

Posture estimating apparatus, posture estimating method and storing medium

An object detection apparatus comprises a detection unit configured to calculate a detection likelihood from each of the plurality of frame images obtained by an image obtaining unit, and to detect a target object from each of the frame images based on the detection likelihood; and a tracking unit configured to calculate a tracking likelihood of the target object from each of the plurality of frame images, and to track the target object over the plurality of frame images based on the tracking likelihood, wherein the detection unit detects the target object from the frame images obtained by the image obtaining unit based on the tracking likelihood of the target object that is calculated by the tracking unit from the frame images, and the detection likelihood of the target object that is calculated by the detection unit from the frame images.

Object detection apparatus, method for controlling the object detection apparatus, and storage medium

An object detection apparatus includes a first detection unit configured to detect a first portion of an object from an input image, a second detection unit configured to detect a second portion different from the first portion of the object, a first estimation unit configured to estimate a third portion of the object based on the first portion, a second estimation unit configured to estimate a third portion of the object based on the second portion, a determination unit configured to determine whether the third portions, which have been respectively estimated by the first and second estimation units, match each other, and an output unit configured to output, if the third portions match each other, a detection result of the object based on at least one of a detection result of the first or second detection unit and an estimation result of the first or second estimation unit.

Object detection apparatus and method therefor

An image processing apparatus for extracting a contour of an object which extracts boundary candidate points from the image and sets reference areas each having one of boundary candidate points as a center and includes small areas. A first reference area is set from the reference areas and a first small area is set from small areas included in the first reference area. From reference areas, a second reference area is set, whose feature is similar to that of the first reference area and as a second small area, a small area is set which has a feature amount similar to that of the first small area among small areas included in the second reference area. The boundary candidate points is tracked to extract the contour of the object based on the first reference area, the second reference area, the first small area, and the second small area.

Image processing apparatus, image processing method, and program

An image processing apparatus includes an image input unit configured to input an image in which a real space is captured by an image capturing apparatus, an image recognition unit configured to recognize a situation in the real space captured in the input image, an image recording unit configured to record the input image, an image selection unit configured to select an image used for image communication from a plurality of images including images recorded by the image recording unit in the past based on a recognition result of the input image, and an image output unit configured to modify the selected image and output the modified image.

Growing community of inventors

Kawasaki, Japan

Kenji Tsukamoto