Canon Kabushiki Kaisha

Hidetoshi Izawa

Ritsuko Otake

Tomoya Honjo

From an input image, a candidate area in which an object exists is acquired. Furthermore, a confidence score indicating a possibility that the object exists and a class probability are acquired. An overlap ratio between candidate areas is calculated for each combination of two arbitrary detection results, and a combination of detection results with an overlap ratio equal to or larger than a threshold value is output as an overlap-detected group. A candidate area used as a representative area is determined from detection results included in the overlap-detected group based on a confidence score. Each class index is calculated based on the overlap ratio with respect to the representative area, and a class with the highest class index is determined as the class of the representative area.

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Kanagawa, Japan

Hidetoshi Izawa