DATA COLLECTION SYSTEM AND DATA COLLECTION METHOD FOR ADDITIONAL LEARNING

To provide a technique to efficiently collect data for additional learning.SOLUTION: A data collection system for additional learning of the present invention comprises: an image processing function unit that performs image processing of recognizing and tracking a target object included in images ob...

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1. Verfasser: FUJII MIYUKI
Format: Patent
Sprache:eng ; jpn
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Zusammenfassung:To provide a technique to efficiently collect data for additional learning.SOLUTION: A data collection system for additional learning of the present invention comprises: an image processing function unit that performs image processing of recognizing and tracking a target object included in images obtained by photographing a predetermined area; and a storage processing function unit that stores the data for additional learning of the image processing. The storage processing function unit temporarily stores data, calculates a predetermined index from the temporarily stored data, performs priority calculation processing based on the index, and performs storage determination processing on the temporarily stored data. When a data amount in an additional learning data unit is less than a threshold, the storage determination processing stores the temporarily stored data in the additional learning data unit, and when the data amount in the additional learning data unit is equal to or more than the threshold, compares the temporarily stored data with data with the lowest priority of the data stored in the additional learning data unit through the priority calculation processing, and deletes the data with the lower priority.SELECTED DRAWING: Figure 1 【課題】本発明では、追加学習用のデータを効率よく収集する技術を提供することを目的とする。【解決手段】本発明の追加学習用のデータ収集システムは、所定エリアを撮影した映像に含まれる対象物体を認識し追跡する画像処理をする画像処理機能部と、前記画像処理の追加学習用のデータを蓄積する蓄積処理機能部とを備える。蓄積処理機能部は、データを一時蓄積し、一時蓄積データから所定の指標を算出し、指標に基づいて優先順位算出処理を行い、かつ一時蓄積データの蓄積判断処理を行う。蓄積判断処理は、追加学習用データ部のデータ量が閾値未満の場合には、一時蓄積データを追加学習用データ部に蓄積し、追加学習用データ部のデータ量が閾値以上の場合には、一時蓄積データと、追加学習用データ部に蓄積されたデータのうち優先順位が最も低いデータを優先順位算出処理により比較し、優先順位の低い方のデータを削除する。【選択図】図1