Nec Corporation

Tomokazu Kaneko

Soma Shiraishi

Ryosuke Sakai

Katsuhiko Takahashi

Takami Sato

Yu Nabeto

Makoto Terao

In a learning data generation device, an acquisition means acquires a first image corresponding to an image obtained by photographing one or more objects arranged in a predetermined arrangement state, and first information corresponding to information indicating the predetermined arrangement state in the first image. An image deformation means deforms a second image corresponding to an image of a desired object. An image generation means generates a fourth image having an arrangement state that matches or is similar to the predetermined arrangement state indicated by the first image, by pasting a deformed second image to the first image or a third image corresponding to the image of a position where the desired object is arranged. A learning data generation means generates data including the fourth image and second information corresponding to the information indicating the arrangement state of the object in the fourth image, as learning data.

Learning data generation device, learning data generation method and recording medium

An image acquisition unitacquires a plurality of images. The plurality of images include an object to be inferred. An image cut-out unitcuts out an object region including the object from each of the plurality of images acquired by the image acquisition unit. An importance generation unitgenerates importance information by processing the object region cut out by the image cut-out unit. The importance information indicates the importance of the object region when an object inference model is generated, and is generated for each object region, that is, for each image acquired by the image acquisition unit. A learning data generation unitstores a plurality of object regions cut out by the image cut-out unitand a plurality of pieces of importance information generated by the importance generation unitin a learning data storage unitas at least a part of the learning data.

Generating learning data from important, cut-out object regions

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Tokyo, Japan

Tomokazu Kaneko