Hitachi, Ltd.

Hitachi Solutions, Ltd.

Ziwei Deng

Naoto Akira

Tomokazu Murakami

Quan Kong

Tomoaki Yoshinaga

An area extraction method includes acquiring a captured image, generating a feature map using the captured image, extracting a candidate bounding box indicating an area in which an object exists in the captured image using the feature map, a segmentation step of generating a mask that is a bounding box indicating the area in which the object exists using the feature map and the candidate bounding box, acquiring input information which is input by a user regarding the object in the captured image, extracting the candidate bounding box using the feature map and the input information, and updating the feature map using the candidate bounding box extracted in the area estimation step and the input information. Wherein the candidate bounding box can be extracted further using the mask generated in the segmentation step, and the feature map can be updated using the mask generated in the segmentation step.

Area extraction method and area extraction system

Provided are: an amodal segmentation unit that generates a set of first amodal masks indicating a probability that a particular pixel belongs to a relevant object for each of objects, with respect to an input image in which a plurality of the objects partially overlap; an overlap segmentation unit that generates an overlap mask corresponding only to an overlap region where the plurality of objects overlap in the input image based on an aggregate mask obtained by combining the set of first amodal masks generated for each of the objects and a feature map generated based on the input image; and an amodal mask correction unit that generates and outputs a second amodal mask, which includes an annotation label indicating a category of each of the objects corresponding to a relevant pixel, for each of pixels in the input image using the overlap mask and the aggregate mask.

Image processing device, image processing method, and image processing system

In a current image processing environment, providing feedback for a user operation is slow, and a user cannot confirm the result of the operation in real time. Thus, the user interrupts the operation every time the user confirms the feedback, and a time period for performing image processing is long. An image processing device includes a guidance information generator. The guidance information generator acquires trajectory information to be used to segment an image object on an image input from a user, generates guidance information indicating a segmentation region desired by the user based on the trajectory information, and presents the segmentation region based on a user's intention in real-time. The guidance information generator provides a function of smoothly continuously segmenting an image object.

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Tokyo, Japan

Ziwei Deng