第七章 結論與未來工作
第二節 未來工作
儘管本實驗可經由視覺追蹤的方式長時間的拍攝嬰兒的活動影片,也能在從 活動影片中監測出嬰兒的活動量,但仍有些需要改進的地方。首先,目前實驗中 仍有多項參數需要人工的方式設定,例如:安全範圍的大小與背景訓練之時間、建 立嬰兒追蹤模型的時間、嬰兒之體重。這些都是會受到家中環境、使用對象以及 設備架設的不同而有所更動的參數,若能改為自動設定且動態調整,才能加強系 統對各種室內環境與使用對象之適應能力,也能讓使用者在使用上更加便利。另 外,在建立追蹤特徵模型時,擷取的特徵是否具代表性取決於室內光線變化的穩 定度,若是在建立追蹤模型與追蹤時室內的光線變化過大,則可能導致追蹤失 敗,此一現象尚待解決。
此外,本系統所使用的搜尋法雖然已經過改良與加速,但仍有進步的空間,
未來可以嘗試其他的搜尋方法,讓系統的搜尋速度加快且仍保優良的搜尋品質。
追蹤時系統尚有一個待突破的地方,當嬰兒在本研究所設定的畫面安全範圍邊界 活動時,依照目前本系統在控制鏡頭移動之決策方法可能導致鏡頭來回於二個鏡 位間移動,雖然此狀況並不常發生,但若出現此現象則會增加追蹤失敗的可能 性。而有關活動量特徵的擷取,目前系統在鏡頭移動時所使用的活動量特徵仍不 夠全面且正確性也稍嫌不足,需增加更多具代表性的特徵來描述鏡頭移動時嬰兒 的活動狀況。上述之問題若能得到加強,會使系統的穩定度更佳,進而達成遠程 的目標。本系統在未來遠程之工作則如下所述:
(A)加入嬰兒習性預測控制鏡頭追蹤
系統已可透過鏡位變換前嬰兒的移動軌跡來預測鏡頭追蹤的方向,但此一軌 跡侷限在鏡頭拍攝範圍內的移動狀況,然而根據本研究長期拍攝嬰兒活動之影片 心得,發現嬰兒在學習不同動作時,在整個活動空間中會出現類似的活動軌跡,
例如:當嬰兒在學步的階段,會傾向於爬行至家具位置附近然後以手扶著家具學 步。上述之活動路徑對本系統來說是跨鏡位的資訊,無法從單一畫面中取得此結 果。因此未來若系統能由更廣的角度出發,學習嬰兒不同階段的活動習性,則能
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利用此資訊來控制鏡頭進行追蹤,不僅提高追蹤的正確率,也能使鏡頭在整個監 控的過程中有更順暢的移動方式進而增加活動量測量之正確性。
(B)增加實驗對象與環境多元化之考量
目前僅有 4 位嬰兒 (4 種室內環境) 在本系統之實驗影片中,然而每個家庭或 幼兒照護中心的大小不同,若遇到更大的環境,可望加入二台以上之攝影機同時 進行嬰兒追蹤與活動量的測量,屆時還須考量不同攝影機之間的溝通。另外,目 前實驗對象僅限本國之嬰兒,未來若能增加實驗對象的多元性,甚至能同時追蹤 多位嬰兒並同時對多位嬰兒進行活動量監測,則系統能適用的對象與環境會更加 廣泛,並能提升其實用性。
(C)透過長期活動量監測建立嬰兒活動量之常態模型
現階段的實驗結果,已有嬰兒從 7 個月至 12 個月的活動影片,然而實驗的 樣本數不足,無法建立出嬰兒從 4 個月至一歲的活動量常態模型。在無常模的情 況下,嬰兒的活動狀況是否異常,需要由專業人士根據活動量監測之結果進行判 斷。但是未來若能建立此常模,則能根據系統目前監測到的活動量,對應此常模 來判斷嬰兒的活動狀況是否出現過量或不足的跡象。
(D)其它嬰兒監控系統之整合
目前市面上已有許多應用於嬰兒之室內監控系統,例如:嬰兒危險偵測、呼 吸頻率偵測等等。若能將系統整合為一,則能利用同一監控設備達到日間活動量 監測、睡眠時呼吸偵測與日常危險偵測三樣功能,成為全方位的室內嬰兒監控系 統。
總而言之,本論文所提出的方法,可以正確的測量嬰兒之活動量,不僅能測 量每個當下嬰兒的 METs 值,且也自動將活動期間的總熱量消耗與活動等級計算 出來,若將來能完成上述之改良,則能讓整套系統更加完善且具實用性。不僅幫 助嬰兒在訓練身體與肢體活動的過程更加有效且安全。此外,長期的記錄嬰兒身 體活動狀況也有利於在就醫時提供正確的治療資訊,使醫師做出正確的診斷。
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