WEKO3
アイテム
Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network
http://hdl.handle.net/10458/0002001498
http://hdl.handle.net/10458/0002001498a98a24a0-6883-4210-aaa8-e72847af260b
| 名前 / ファイル | ライセンス | アクション |
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| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||||||||||||||||||||||
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| 公開日 | 2025-07-21 | |||||||||||||||||||||||||||||||
| タイトル | ||||||||||||||||||||||||||||||||
| タイトル | Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network | |||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
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| 言語 | eng | |||||||||||||||||||||||||||||||
| キーワード | ||||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
| キーワード | Color point cloud | |||||||||||||||||||||||||||||||
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| 言語 | en | |||||||||||||||||||||||||||||||
| キーワード | PointNet++ | |||||||||||||||||||||||||||||||
| キーワード | ||||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
| キーワード | Siamese network | |||||||||||||||||||||||||||||||
| キーワード | ||||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
| キーワード | Triplet loss | |||||||||||||||||||||||||||||||
| 資源タイプ | ||||||||||||||||||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||||||||||||||||||
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| アクセス権 | open access | |||||||||||||||||||||||||||||||
| 著者 |
Kyaw, Pyae Phyo
× Kyaw, Pyae Phyo
× パイ, テイン
WEKO
35357
× 相川, 勝
WEKO
12201
× 小林, 郁雄
WEKO
5214
× ティ ティ ズイン
WEKO
31575
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| 内容記述タイプ | Abstract | |||||||||||||||||||||||||||||||
| 内容記述 | Cattle health monitoring and management systems are essential for farmers and veterinarians, as traditional manual health checks can be time-consuming and labor-intensive. A critical aspect of such systems is accurate cattle identification, which enables effective health monitoring. Existing 2D vision-based identification methods have demonstrated promising results; however, their performance is often compromised by environmental factors, variations in cattle texture, and noise. Moreover, these approaches require model retraining to recognize newly introduced cattle, limiting their adaptability in dynamic farm environments. To overcome these challenges, this study presents a novel cattle identification system based on color point clouds captured using RGB-D cameras. The proposed approach employs a hybrid detection method that first applies a 2D depth image detection model before converting the detected region into a color point cloud, allowing for robust feature extraction. A customized lightweight tracking approach is implemented, leveraging Intersection over Union (IoU)-based bounding box matching and mask size analysis to consistently track individual cattle across frames. The identification framework is built upon a hybrid PointNet ++ Siamese Network trained with a triplet loss function, ensuring the extraction of discriminative features for accurate cattle identification. By comparing extracted features against a pre-stored database, the system successfully predicts cattle IDs without requiring model retraining. The proposed method was evaluated on a dataset consisting predominantly of Holstein cow along with a few Jersey cows, achieving an average identification accuracy of 99.55% over a 13-day testing period. Notably, the system can successfully detect and identify unknown cattle without requiring model retraining. This cattle identification research aims to integrate the comprehensive cattle health monitoring system, encompassing lameness detection, body condition score evaluation, and weight estimation, all based on point cloud data and deep learning techniques. | |||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
| 書誌情報 |
en : Scientific Reports 巻 15, p. 21938, 発行日 2025-07-01 |
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| 出版者 | ||||||||||||||||||||||||||||||||
| 出版者 | Springer Science and Business Media LLC | |||||||||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||||||||||||||||||||||
| 収録物識別子 | 20452322 | |||||||||||||||||||||||||||||||
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| 関連タイプ | isVersionOf | |||||||||||||||||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||||||||||||||||||
| 関連識別子 | https://doi.org/10.1038/s41598-025-08277-8 | |||||||||||||||||||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||||||||||||||||||
