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姓名 沈桓慶(Huan-Ching Shen) 查詢紙本館藏 畢業系所 資訊工程學系 論文名稱 基於聯合嵌入之雙手配對與追蹤系統
(A Hands Pairing and Tracking System base on Associative Embedding)相關論文 檔案 [Endnote RIS 格式] [Bibtex 格式] [相關文章] [文章引用] [完整記錄] [館藏目錄] [檢視] [下載]
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摘要(中) 手部追蹤旨在預測影像序列中多個手的軌跡,對於空中手寫、手語辨識及手勢辨識等應用具有重要的意義,而將雙手分組可以使上述應用實現更複雜的功能。
本論文提出基於YOLOv3和聯合嵌入的方法,整合多目標追蹤和關節點檢測的單階段類神經網路模型和演算法,實現實時的多人雙手追蹤。摘要(英) Hand tracking aims to predict the trajectory of multiple hands in an image sequence, which is of great significance for applications such as air handwriting, sign language recognition and gesture recognition, and grouping the hands can enable the above applications to achieve more complex functions.
This paper proposes a single-stage neural network model and algorithm based on YOLOv3 and associative embedding, integrating multi-target tracking and joint point detection, to achieve real-time multi-person hand tracking.關鍵字(中) ★ 深度學習
★ 偵測系統
★ 手勢追蹤
★ 物件偵測
★ 類神經網路
★ 聯合嵌入關鍵字(英) ★ deep learning
★ detection system
★ gesture tracking
★ object detection
★ neural network
★ associative embedding論文目次 頁次
中文摘要......................................................................................................................... iii
英文摘要......................................................................................................................... v
謝誌................................................................................................................................. vii
目錄................................................................................................................................. ix
圖目錄............................................................................................................................. xi
表目錄.............................................................................................................................xiii
一、 緒論......................................................................................................... 1
1.1 研究動機 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究目的與方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 論文架構 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
二、 相關文獻與背景知識............................................................................. 3
2.1 物件偵測 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 非極大值抑制 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.3 聯合嵌入 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
三、 研究架構................................................................................................. 9
3.1 研究流程 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.2 模型結構 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
3.3 雙手偵測 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3.4 雙手配對與追蹤 . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
四、 實驗結果................................................................................................. 15
4.1 實驗環境 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.2 測試結果 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.3 實驗數據 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
五、 結論......................................................................................................... 19
參考文獻......................................................................................................................... 21
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(ICPR’06), volume 3, pages 850–855, 2006.指導教授 范國清(Kuo-Chin Fan) 審核日期 2021-5-21 推文 facebook plurk twitter funp google live udn HD myshare reddit netvibes friend youpush delicious baidu 網路書籤 Google bookmarks del.icio.us hemidemi myshare