TWI784451B - Image conversion system and image conversion method - Google Patents
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本發明是關於一種轉換影像的應用,特別是關於一種影像轉換系統及影像轉換方法。The invention relates to an application of image conversion, in particular to an image conversion system and an image conversion method.
傳統攝像機影像偵測到物件時,需要透過攝像機定位、校正等方式才能達到將物件的空間位置座標轉換至平面圖上,若是攝像機種類改變、型號更新、擺放位置被改變或攝像機內部參數改變,則會需要重做定位和校正。然而,定位和校正往往需要人員至現場更換攝像機並當場量測攝像機位置才能達成,十分不便。When an object is detected by a traditional camera image, it is necessary to use camera positioning, calibration, etc. to convert the spatial position coordinates of the object to the plan. If the camera type changes, the model is updated, the placement position is changed, or the internal parameters of the camera are changed, then Positioning and alignment will need to be redone. However, positioning and calibration often requires personnel to replace the camera on site and measure the position of the camera on the spot, which is very inconvenient.
此外,多攝像機轉換座標至同一平面圖時,亦會發生平面圖上座標拼接的問題。傳統座標轉換方法,需要先將攝像機做適當的影像轉換,例如將魚眼攝像機拍攝的影像轉換為方形平面,以對應真實地圖,再量測攝像機本身的安裝高度和世界地圖對應的安裝位置,即可取得影像對應平面圖的涵蓋範圍,接著,攝像機影像內的物件偵測位置即可轉換至平面圖上。當攝像機數量較多時,需要精準量測攝像機之間的涵蓋範圍,確保影像的涵蓋範圍彼此不干擾,否則會發生同一物件出現在二個攝像機,則需要處理物件歸屬於哪個座標的問題。In addition, when the coordinates of multiple cameras are converted to the same plan, the problem of coordinating coordinates on the plan will also occur. The traditional coordinate conversion method needs to perform appropriate image conversion on the camera first, such as converting the image taken by the fisheye camera into a square plane to correspond to the real map, and then measure the installation height of the camera itself and the installation position corresponding to the world map, namely The coverage area corresponding to the floor plan of the image can be obtained, and then the detected position of the object in the camera image can be converted to the floor plan. When there are a large number of cameras, it is necessary to accurately measure the coverage of the cameras to ensure that the coverage of the images does not interfere with each other. Otherwise, the same object will appear in two cameras, and it is necessary to deal with the problem of which coordinates the object belongs to.
因此,如何設定一個新的影像轉換方法,無關攝像機本身種類、參數、安裝位置等,只需要攝像機安裝完成之後,即能從影像直接設定與平面圖的關聯性,已成為本領域需解決的問題之一。Therefore, how to set a new image conversion method has become one of the problems to be solved in this field, regardless of the type, parameters, installation location, etc. of the camera itself. It only needs to be able to directly set the correlation with the floor plan from the image after the camera is installed. one.
為了解決上述的問題,本揭露內容之一態樣提供了一種影像轉換系統。影像轉換系統包含一攝像機以及一處理器。攝像機用以拍攝一影像;其中,該影像中包含複數個定位標籤圖樣。處理器用以接收影像,透過辨識此些定位標籤圖樣,依據此些定位標籤圖樣產生一影像特定區域,將此影像特定區域轉換到一平面圖的一平面特定區域。In order to solve the above problems, an aspect of the present disclosure provides an image conversion system. The image conversion system includes a camera and a processor. The camera is used to shoot an image; wherein, the image includes a plurality of positioning label patterns. The processor is used for receiving the image, by identifying the positioning tag patterns, generating a specific image area according to the positioning tag patterns, and converting the specific image area into a plane specific area of a plan view.
於一實施例中,影像轉換系統更包含一室內定位裝置。室內定位裝置用以透過複數個定位標籤各自與複數個基地台傳輸一訊號,此些基地台各自接收到該些訊號後,將此些訊號的強度傳送至處理器,處理器以一三角定位演算法計算此些定位標籤各自於一空間中對應的相對位置。In one embodiment, the image conversion system further includes an indoor positioning device. The indoor positioning device is used to transmit a signal with a plurality of base stations through a plurality of positioning tags. After receiving the signals, the base stations transmit the strength of the signals to the processor, and the processor performs a triangulation calculation method to calculate the corresponding relative positions of these positioning tags in a space.
於一實施例中,處理器取得三個該些定位標籤於空間中的三個不同的相對位置,或是取得此些定位標籤之一者於空間中移動至三次到不同位置,所得到三個不同的相對位置,將此三個不同的相對位置連線,以得到轉換到空間中的一三角型平面。In one embodiment, the processor obtains three different relative positions of the positioning tags in space, or obtains one of the positioning tags and moves to different positions three times in space, and obtains three Different relative positions, connect these three different relative positions to obtain a triangular plane transformed into space.
於一實施例中,處理器將三角型平面的各頂點對應至此些定位標籤圖樣的位置後,得到三角型平面於影像中對應的位置,再將三角型平面於影像中對應的位置轉換到平面圖上。In one embodiment, after the processor corresponds each vertex of the triangular plane to the position of these positioning label patterns, the corresponding position of the triangular plane in the image is obtained, and then the corresponding position of the triangular plane in the image is converted into a plan view superior.
於一實施例中,一完整平面特定區域由複數個三角型平面構成,當完整平面特定區域建立完成,則處理器將影像輸入已訓練完成的一深度學習網路,深度學習網路輸出一框選範圍,處理器計算框選範圍之最底部線條的一中心點位置,並追蹤中心點位置的一移動路徑。In one embodiment, a specific area of a complete plane is composed of a plurality of triangular planes. When the specific area of the complete plane is established, the processor inputs the image into a trained deep learning network, and the deep learning network outputs a frame The processor calculates a center point position of the bottommost line of the frame selection range, and tracks a movement path of the center point position.
本揭露內容之另一態樣提供了一種影像轉換方法。影像轉換方法包含以下步驟:拍攝一影像;其中,影像中包含複數個定位標籤圖樣;接收影像,透過辨識此些定位標籤圖樣,並依據此些定位標籤圖樣以產生一影像特定區域;以及將影像特定區域轉換到一平面圖的一平面特定區域。Another aspect of the disclosure provides an image conversion method. The image conversion method includes the following steps: taking an image; wherein, the image includes a plurality of positioning label patterns; receiving the image, identifying the positioning label patterns, and generating a specific area of the image according to the positioning label patterns; and transforming the image The specific area is converted to a plane specific area of a plan.
於一實施例中,影像轉換方法更包含:透過複數個定位標籤各自與複數個基地台傳輸一訊號,此些基地台各自接收到此些訊號後,將此些訊號的強度傳送至一處理器,處理器以一三角定位演算法計算此些定位標籤各自於一空間中對應的相對位置。In one embodiment, the image conversion method further includes: transmitting a signal to a plurality of base stations through a plurality of positioning tags, and each of the base stations transmits the strength of the signals to a processor after receiving the signals The processor uses a triangulation algorithm to calculate the corresponding relative positions of the positioning tags in a space.
於一實施例中,影像轉換方法更包含:取得三個此些定位標籤於空間中的三個不同的相對位置,或是取得此些定位標籤之一者於空間中移動至三次到不同位置,所得到三個不同的相對位置;以及將此三個不同的相對位置連線,以得到轉換到空間中的一三角型平面。In one embodiment, the image conversion method further includes: obtaining three different relative positions of the positioning tags in space, or obtaining one of the positioning tags to move three times to different positions in space, Three different relative positions are obtained; and connecting the three different relative positions to obtain a triangular plane transformed into space.
於一實施例中,影像轉換方法更包含:將三角型平面的各頂點對應至此些定位標籤圖樣的位置後,得到三角型平面於影像中對應的位置,再將三角型平面於影像中對應的位置轉換到平面圖上。In one embodiment, the image conversion method further includes: after corresponding the vertices of the triangular planes to the positions of the positioning label patterns, the corresponding positions of the triangular planes in the image are obtained, and then the corresponding positions of the triangular planes in the image are obtained. Location converted to floor plan.
於一實施例中,一完整平面特定區域由複數個三角型平面構成,當完整平面特定區域建立完成,則將影像輸入已訓練完成的一深度學習網路,深度學習網路輸出一框選範圍;計算框選範圍之最底部線條的一中心點位置;以及將影像特定區域轉換到一平面圖的一平面特定區域。In one embodiment, a specific area of a complete plane is composed of a plurality of triangular planes. When the specific area of the complete plane is established, the image is input to a deep learning network that has been trained, and the deep learning network outputs a frame selection range ; Calculating a center point position of the bottommost line of the marquee range; and converting a specific area of the image to a specific area of a plane of a plan view.
本發明所示之影像轉換系統及影像轉換方法,無論是魚眼攝像機或槍型攝像機所拍攝的影像,皆可將這些影像轉換至同一個平面圖上,以得知攝像機相機在平面圖上的覆蓋範圍,每個覆蓋範圍都是以多個三角形平面組成,本發明所示之影像轉換系統及影像轉換方法不需要知道多台攝像機任何的參數和位置,不同鏡頭覆蓋範圍無需定位也無需校正,即可將多台相同或不同的攝像機拍攝範圍(即完整平面特定區域)轉換到同一個平面圖上,大幅減少佈建攝像機時,人力所花費的時間。The image conversion system and image conversion method shown in the present invention, no matter the images taken by the fisheye camera or the bullet camera, can convert these images to the same plan to know the coverage of the camera on the plan , each coverage area is composed of multiple triangular planes. The image conversion system and image conversion method shown in the present invention do not need to know any parameters and positions of multiple cameras, and the coverage areas of different lenses do not need to be positioned or corrected. Convert the shooting range of multiple identical or different cameras (that is, a specific area of a complete plane) to the same floor plan, greatly reducing the time spent on manpower when deploying cameras.
此外,處理器將攝像機所拍攝到的範圍自動轉換到平面圖上之後,處理器能夠自動透過影像處理方法追蹤完整平面特定區域中的人體位移,此可以應用到長照中心,由於一般年長者有不習慣配戴電子裝置的特性,藉由本發明所示之影像轉換系統及影像轉換方法,能夠應用完整平面特定區域中標記的中心點位置(即人體位置),以追蹤年長者的移動路徑,有助於判斷年長者是否有失智狀態出現。In addition, after the processor automatically converts the range captured by the camera to the plane map, the processor can automatically track the human body displacement in a specific area of the complete plane through image processing methods. This can be applied to long-term care centers, because the elderly generally have different Due to the habit of wearing electronic devices, the image conversion system and image conversion method shown in the present invention can use the center point position (that is, the position of the human body) marked in the specific area of the complete plane to track the moving path of the elderly, which is helpful It is used to judge whether the elderly have dementia.
以下說明係為完成發明的較佳實現方式,其目的在於描述本發明的基本精神,但並不用以限定本發明。實際的發明內容必須參考之後的權利要求範圍。The following description is a preferred implementation of the invention, and its purpose is to describe the basic spirit of the invention, but not to limit the invention. For the actual content of the invention, reference must be made to the scope of the claims that follow.
必須了解的是,使用於本說明書中的”包含”、”包括”等詞,係用以表示存在特定的技術特徵、數值、方法步驟、作業處理、元件以及/或組件,但並不排除可加上更多的技術特徵、數值、方法步驟、作業處理、元件、組件,或以上的任意組合。It must be understood that words such as "comprising" and "comprising" used in this specification are used to indicate the existence of specific technical features, values, method steps, operations, components and/or components, but do not exclude possible Add more technical characteristics, values, method steps, operation processes, components, components, or any combination of the above.
於權利要求中使用如”第一”、"第二"、"第三"等詞係用來修飾權利要求中的元件,並非用來表示之間具有優先權順序,先行關係,或者是一個元件先於另一個元件,或者是執行方法步驟時的時間先後順序,僅用來區別具有相同名字的元件。Words such as "first", "second", and "third" used in the claims are used to modify the elements in the claims, and are not used to indicate that there is an order of priority, an antecedent relationship, or an element An element preceding another element, or a chronological order in performing method steps, is only used to distinguish elements with the same name.
請參照第1~5圖,第1圖係依照本發明一實施例繪示影像轉換系統100之方塊圖。第2圖係依照本發明一實施例繪示影像轉換系統200之方塊圖。第3圖係依照本發明一實施例繪示影像轉換方法300之示意圖。第4圖係依照本發明一實施例繪示室內定位方法之示意圖。第5圖係依照本發明一實施例繪示室內定位方法之示意圖。Please refer to FIGS. 1-5. FIG. 1 is a block diagram of an
如第1圖所示,影像轉換系統100包含一攝像機10及一處理器20。如第2圖所示,影像轉換系統200中包含多個攝像機10、12、處理器20、多個基地台AP1~AP4及一定位標籤TAG0。As shown in FIG. 1 , the
於第1~2圖中的攝像機10、12可以是魚眼攝像機、槍型攝像機或其他種類攝像機。於一實施例中,攝像機10、12通訊耦接於處理器20,使得攝像機10、12能將擷取到的影像傳送給處理器20,通訊耦接可以是透過有線或無線的傳輸方式。The
於一實施例中,第1~2圖中的處理器20可由積體電路如微控制單元(micro controller)、微處理器(microprocessor)、數位訊號處理器(digital signal processor)、特殊應用積體電路(application specific integrated circuit,ASIC)或一邏輯電路來實施。於一實施例中,第1~2圖中的處理器20可以位在一伺服器、一桌電、一筆電或其他具有運算功能的電子裝置中。In one embodiment, the
於一實施例中,基地台AP1~AP4可以是無線基地台(又稱「無線AP」,其中AP是指 “Access Point”)。In one embodiment, the base stations AP1-AP4 may be wireless base stations (also called "wireless AP", where AP refers to "Access Point").
請一併參照第2~4圖,室內定位可以應用Beacon無線訊號的系統技術或無線射頻識別系統(Radio Frequency Identification,RFID)以實現,以下以Beacon無線訊號的系統技術為例,然本領域具通常知識者應能理解,只要是能進行室內定位的方法皆可以應用於此。Please also refer to Figures 2-4. Indoor positioning can be realized by using Beacon wireless signal system technology or radio frequency identification (Radio Frequency Identification, RFID). The following uses Beacon wireless signal system technology as an example. Generally, knowledgeable persons should be able to understand that any method that can perform indoor positioning can be applied here.
於步驟310中,攝像機10拍攝一影像;其中,影像中包含複數個定位標籤圖樣。In
於一實施例中,影像轉換系統200的室內定位裝置用以透過多個定位標籤各自與一個或多個基地台(例如基地台AP1~AP4)傳輸一訊號,此些基地台各自接收到此些訊號後,將此些訊號的強度傳送至處理器20,處理器20以一三角定位演算法計算此些定位標籤各自於一空間中對應的相對位置。由於三角定位演算法為已知的空間定位方法,故此處不贅述之。In one embodiment, the indoor positioning device of the
於一實施例中,如第4圖所示,基地台AP1~AP4可以佈署在空間SP的四個不同的位置,定位標籤TAG0可以放置在空間SP中的任何位置。Beacon無線訊號的系統技術的實現需要一個定位標籤TAG0(能夠主動發射訊號的標籤,Beacon tag)及基地台AP1~AP4(應用至少三個基地台以實現三角定位演算法)。In one embodiment, as shown in FIG. 4 , the base stations AP1 - AP4 can be deployed in four different positions in the space SP, and the positioning tag TAG0 can be placed in any position in the space SP. The implementation of Beacon wireless signal system technology requires a positioning tag TAG0 (a tag capable of actively transmitting signals, Beacon tag) and base stations AP1~AP4 (applying at least three base stations to realize the triangulation algorithm).
於一實施例中,定位標籤TAG0透過Beacon的無線訊號傳輸技術發送訊號,使基地台AP1~AP4接收到訊號,基地台AP1~AP4可以將接收到的訊號的接收訊號強度指示(Received Signal Strength Indication,RSSI)傳送到處理器20或是與基地台AP1~AP4通訊耦接的定位伺服器,使收到這些接收訊號強度指示的處理器20或定位伺服器可以基於訊號場強指示定位原理,依據每個基地台AP1~AP4接收到訊號的強弱,算出定位標籤TAG0在空間SP中的位置。於一實施例中,若是定位伺服器計算出定位標籤TAG0在空間SP中的位置,定位伺服器會將此位置傳送給處理器20。In one embodiment, the positioning tag TAG0 sends a signal through Beacon's wireless signal transmission technology, so that the base stations AP1~AP4 receive the signal, and the base station AP1~AP4 can indicate the received signal strength (Received Signal Strength Indication) of the received signal , RSSI) to the
換言之,設置好基地台AP1~AP4後,處理器20或定位伺服器可以基於訊號場強指示定位原理配合三角定位演算法算出定位標籤TAG0在空間SP中的位置。In other words, after the base stations AP1-AP4 are set up, the
於一實施例中,如第5圖所示,空間SP中可以有三個或三個以上的定位標籤TAG1~TAG3,為方便說明,以下以三個定位標籤TAG1~TAG3為例。In one embodiment, as shown in FIG. 5 , there may be three or more positioning tags TAG1 - TAG3 in the space SP. For convenience of description, three positioning tags TAG1 - TAG3 are taken as an example below.
於一實施例中,處理器20或定位伺服器可以依據前述方式,依據三角定位演算法分別算出此三個定位標籤TAG1~TAG3各自在空間SP中的位置,並將此三個定位標籤TAG1~TAG3各自在空間SP中的位置以線段連起來,成為一個三角型平面TR。接著,處理器20需要將三角型平面TR實際對應到攝像機10或12拍攝的影像範圍中。In one embodiment, the
於一實施例中,如第5圖所示,處理器20取得三個定位標籤TAG1~TAG3於空間SP中的三個不同的相對位置,或是取得定位標籤TAG1~TAG3之一者於空間SP中移動至三次到不同位置(例如移動定位標籤TAG1到不同的位置三次),所得到三個不同的相對位置,將此三個不同的相對位置連線,以得到空間SP中的一三角型平面TR,將三角型平面TR的三個頂點與攝像機10擷取之影像600中的定位標籤圖樣各自對應,以得到影像600中的三角型平面TR’,再將三角型平面TR’轉換到平面圖700中的一三角型平面TR’’。此部分將於後續詳述之。In one embodiment, as shown in FIG. 5, the
於步驟320中,處理器20接收影像600,透過辨識此些定位標籤圖樣,並依據此些定位標籤圖樣產生一影像特定區域(例如三角型平面TR’)。In
請參閱第6圖,第6圖係依照本發明一實施例繪示攝像機10擷取之影像600之示意圖。於一實施例中,為了讓攝像機10容易尋找定位標籤TAG1~TAG3,事先將定位標籤TAG1~TAG3上分別繪製數字“1”、“2”、“3”作為定位標籤圖樣,攝像機10拍攝到的影像600中包含此些定位標籤圖樣。Please refer to FIG. 6 . FIG. 6 is a schematic diagram illustrating an
於一實施例中,定位標籤TAG1~TAG3上不一定繪製數字作為定位標籤圖樣,定位標籤TAG1~TAG3上也可以繪製任何具識別性的圖案作為定位標籤圖樣,例如紅色圓形、綠色方形、黃色三角形…等等圖案。In one embodiment, numbers are not necessarily drawn on the positioning tags TAG1~TAG3 as the positioning tag pattern, and any identifiable pattern can also be drawn on the positioning tags TAG1~TAG3 as the positioning tag pattern, such as red circle, green square, yellow Triangles... and so on.
於一實施例中,處理器20可事先訓練一深度學習網路,深度學習網路例如為卷積神經網路(Convolutional Neural Network,CNN),處理器20事先將攝像機10擷取到的多張影像輸入深度學習網路中,以訓練深度學習網路辨識人體位置。待深度學習網路事先訓練完成後,處理器20將當前擷取到的影像輸入深度學習網路,深度學習網路輸出包含人體位置框選範圍F1、F2的影像600。In one embodiment, the
於一實施例中,處理器20計算框選範圍F1、F2之最底部線條的一中心點位置P1、P2,後續藉由追蹤中心點位置P1、P2可以得知中心點位置P1、P2的移動路徑,其代表人體的移動路徑。In one embodiment, the
於一實施例中,處理器20將三角型平面(例如第5圖中的三角型平面TR)的各頂點對應至此些定位標籤圖樣的位置(例如第6圖所示的定位標籤圖樣“1”、“2”及“3”)後,得到三角型平面TR於影像600中對應的位置(即三角型平面TR’’),再將三角型平面TR於影像600中對應的位置(即三角型平面TR’’)轉換到平面圖700上。In one embodiment, the
於一實施例中,攝像機10將影像600傳送到處理器20,處理器20依據已知的影像辨識方法,以搜尋到影像600中定位標籤TAG1~TAG3各自對應的定位標籤圖樣。In one embodiment, the
於一實施例中,定位標籤TAG1~TAG3在初始時可以貼在桌面、椅子、柱子、櫃子…等比較容易被辨識到的地方,可增加處理器20辨識影像600中定位標籤TAG1~TAG3各自對應的定位標籤圖樣的精準度。In one embodiment, the positioning tags TAG1~TAG3 can be attached to the table, chairs, pillars, cabinets, etc., which are relatively easy to be identified at the beginning, and the
處理器20將辨識到的定位標籤TAG1在空間SP中的位置對應到定位標籤圖樣為“1”的位置,將定位標籤TAG2在空間SP中的位置對應到定位標籤圖樣為“2”的位置,將定位標籤TAG3在空間SP中的位置對應到定位標籤圖樣為“3”的位置,於影像600中,可看出定位標籤圖樣為“1”的位置、定位標籤圖樣為“2”的位置及定位標籤圖樣為“3”的位置可連成三角型平面TR’,此三角型平面TR’視為影像特定區域。The
接著,處理器20需要將三角型平面TR’實際對應到室內的一平面圖700上。Next, the
於步驟330中,處理器20將影像特定區域(例如三角型平面TR’)轉換到一平面圖700的一平面特定區域(例如三角型平面TR’’)。In
請參閱第7圖,第7圖係依照本發明一實施例繪示平面圖700之示意圖。於一實施例中,平面圖700中的物件為已知,已知的物件例如有:所有定位標籤圖樣、物件OBJ1~OBJ5、中心點位置P1、P2。Please refer to FIG. 7 , which is a schematic diagram illustrating a
由於平面圖700中已知所有定位標籤圖樣的座標(可以是事先設定的圖資),因此可將影像600中定位標籤圖樣為“1”的位置對應到平面圖700中定位標籤圖樣為“1”的位置、將影像600中定位標籤圖樣為“2”的位置對應到平面圖700中定位標籤圖樣為“2”的位置、將影像600中定位標籤圖樣為“3”的位置對應到平面圖700中定位標籤圖樣為“3”的位置。Since the coordinates of all positioning label patterns are known in the plan view 700 (it can be a pre-set map data), the position of the positioning label pattern "1" in the
於一實施例中,於平面圖700中,定位標籤圖樣為“1”的位置、定位標籤圖樣為“2”的位置及定位標籤圖樣為“3”的位置可連成三角型平面TR’’,此代表三角型平面TR’’是位於攝影機10可拍攝到的範圍內,亦達到將攝影機10拍攝到的影像特定區域(如三角型平面TR’)轉換至平面圖700上的平面特定區域(如三角型平面TR’’)的效果。In one embodiment, in the
藉由重複多次上述步驟,移動多個定位標籤TAG1~TAG3的位置,或是加大定位標籤TAG1~TAG3之間的距離,處理器20可以產生多個三角型平面TR’’,藉此建立出一完整平面特定區域Ra,此平面特定區域Ra代表在平面圖700中,攝像機10可拍攝到的位置。By repeating the above steps several times, moving the positions of multiple positioning tags TAG1~TAG3, or increasing the distance between the positioning tags TAG1~TAG3, the
於一實施例中,完整平面特定區域Ra由多個三角型平面TR’’構成。In one embodiment, the complete plane specific region Ra is composed of a plurality of triangular planes TR''.
於一實施例中,處理器20將多個不同大小即/或不同位置的三角型平面TR’轉換到平面圖700的多個不同大小即/或不同位置的三角型平面TR’’,以生成完整平面特定區域Ra。In one embodiment, the
由上述可知,第5圖中的三角型平面TR是位於空間SP中的三個定位標籤TAG1~TAG3的三維座標連起來而成,將第5圖中的三角型平面TR對應到第6圖的影像600中可生成二維座標的三角型平面TR’,將第6圖的三角型平面TR’的各頂點對應到已知的定位標籤座標的平面圖700中,可在平面圖700中生成三角型平面TR’’。From the above, it can be seen that the triangular plane TR in Figure 5 is formed by connecting the three-dimensional coordinates of the three positioning tags TAG1~TAG3 located in the space SP, and the triangular plane TR in Figure 5 corresponds to that in Figure 6. A triangular plane TR' with two-dimensional coordinates can be generated in the
換言之,只要移動定位標籤TAG1~TAG3至少一者的位置,處理器20即可得到不同大小及/或位置的三角型平面TR’’,重複上述步驟,可建立完整的平面特定區域Ra。In other words, as long as the position of at least one of the positioning tags TAG1-TAG3 is moved, the
於一實施例中,當完整平面特定區域Ra建立完成,則處理器20將影像600輸入已訓練完成的一深度學習網路,此深度學習網路用以框選出影像中的人體範圍。接著,深度學習網路輸出一框選範圍(例如框選範圍F1、F2),處理器20計算框選範圍之最底部線條的一中心點位置(例如中心點位置P1、P2),並追蹤中心點位置的一移動路徑。In one embodiment, when the complete plane specific area Ra is established, the
於一實施例中,處理器20可藉由在平面圖700上以色塊標示三角型平面TR’’,因此色塊的整體可視為完整平面特定區域Ra,完整平面特定區域Ra代表攝像機10的拍攝範圍被轉換到平面圖700上。In one embodiment, the
由此可知,影像轉換方法300不需要知道多台攝像機任何的參數和位置,不同鏡頭(如魚眼攝像機或槍型攝像機)覆蓋範圍無需定位也無需校正,即可應用建立出多塊三角型平面TR’’,將多台相同或不同的攝像機的拍攝範圍(即完整平面特定區域Ra)呈現到同一個平面圖700上。It can be seen that the image conversion method 300 does not need to know any parameters and positions of multiple cameras, and the coverage of different lenses (such as fisheye cameras or bullet cameras) can be applied to establish multiple triangular planes without positioning or correction. TR'', present the shooting ranges of multiple identical or different cameras (that is, the complete plane specific area Ra) on the
於一實施例中,藉由重複上述步驟,出直到定位標籤圖樣不存在影像600中時,代表此組定位標籤TAG1~TAG3的至少一部分位置已超出攝像機10的拍攝範圍,只能有未超出拍攝範圍的部分能被轉換為平面圖700上的部分平面特定區域並以色塊表示之。In one embodiment, by repeating the above steps until the positioning tag pattern does not exist in the
當攝像機10拍攝範圍的邊際都已轉換到平面圖700上時,則將此時的平面圖700上的色塊的整體(由多個不同大小及/或位置的三角型平面TR’’上色後組成)視為完整平面特定區域Ra。When the boundaries of the shooting range of the
由此可知,完整平面特定區域Ra之外的位置是攝像機10沒有拍攝到的位置,那些沒有被拍攝到的位置可以再裝上一或多個攝像機(例如攝像機12)以補足,讓整張平面圖700都被拍攝到。透過上述步驟310~340的影像轉換方法,只需要相機安裝完成之後,即能從相機擷取到的影像設定相機擷取到的影像與平面圖700的關聯性。It can be seen that the position outside the specific area Ra of the complete plane is the position that the
於一實施例中,由於已得到完整平面特定區域Ra,多個基地台AP1~AP4及一定位標籤TAG可以拆除,後續由處理器20應用已知的影像辨識方法,例如以卷積神經網路辨識演算法、 基於區域的卷積神經網路(Regions with CNN,R-CNN)演算法、基於區域的快速卷積神經網路(Fast R-CNN)、基於區域更快卷積神經網路(Faster R-CNN)…等,以追蹤攝像機10所捕捉到的影像中的中心點位置P1、P2,中心點位置P1、P2的移動,藉此可得知人體的移動路徑。In one embodiment, since the complete plane specific area Ra has been obtained, multiple base stations AP1-AP4 and a positioning tag TAG can be removed, and then the
請參閱第8圖,第8圖係依照本發明一實施例繪示人體的移動路徑800之示意圖。如前述,處理器20應用已知的影像辨識方法,以追蹤攝像機10所捕捉到的影像中的中心點位置P1、P2,中心點位置P1、P2的移動,代表人體的移動路徑。Please refer to FIG. 8 . FIG. 8 is a schematic diagram illustrating a moving
此情境可應用於長照中心,在一些有失智狀態的年長者,有時知道自己要往物件OBJ1走,但走一下子,又會忘記自己要往何處走,可能會隨機亂走或是不停繞著一個圓形路徑行走,此為游移狀態。This situation can be applied to long-term care centers. Some elderly people with dementia sometimes know that they are going to the object OBJ1, but after walking for a while, they will forget where they are going, and they may walk randomly or It is walking around a circular path non-stop, this is the wandering state.
在第8圖可看出,中心點位置P1的移動軌跡L1為一直線,代表對應中心點位置P1的人體是直接走到物件OBJ1(例如物件OBJ1為餐桌),中心點位置P2的移動軌跡L2是彎曲迂迴的線段,代表對應中心點位置P2的人體是迂迴的走到物件OBJ1,對應中心點位置P2的人體可能有失智的游移症狀。It can be seen in Figure 8 that the moving track L1 of the central point position P1 is a straight line, which means that the human body corresponding to the central point position P1 walks directly to the object OBJ1 (for example, the object OBJ1 is a dining table), and the moving track L2 of the central point position P2 is The curved and circuitous line segment means that the human body corresponding to the center point P2 walks to the object OBJ1 in a circuitous manner, and the human body corresponding to the center point P2 may have a wandering symptom of dementia.
處理器20透過追蹤攝像機10所捕捉到的影像中的中心點位置P1、P2,可以將中心點位置P1、P2的移動路徑記錄下來並儲存於一儲存裝置(儲存裝置可由唯讀記憶體、快閃記憶體、軟碟、硬碟、光碟、隨身碟、磁帶、可由網路存取之資料庫或熟悉此技藝者可輕易思及具有相同功能之儲存媒體以實現之)。The
藉此,照護人員透過觀察中心點位置P1、P2的移動路徑,可以發現中心點位置P2對應的年長者有游移狀態。照護人員可以視情況選擇是否作進一步的處置,例如照護人員可以特別關注此年長者或通知家人。In this way, the caregiver can find that the elderly person corresponding to the center point P2 is in a state of wandering by observing the moving paths of the center point positions P1 and P2. The caregiver can choose whether to take further treatment according to the situation. For example, the caregiver can pay special attention to the elderly or notify the family.
本發明所示之影像轉換系統及影像轉換方法,無論是魚眼攝像機或槍型攝像機所拍攝的影像,皆可將這些影像轉換至同一個平面圖上,以得知攝像機相機在平面圖上的覆蓋範圍,每個覆蓋範圍都是以多個三角形平面組成,本發明所示之影像轉換系統及影像轉換方法不需要知道多台攝像機任何的參數和位置,不同鏡頭覆蓋範圍無需定位也無需校正,即可將多台相同或不同的攝像機拍攝範圍(即完整平面特定區域)轉換到同一個平面圖上,大幅減少佈建攝像機時,人力所花費的時間。The image conversion system and image conversion method shown in the present invention, no matter the images taken by the fisheye camera or the bullet camera, can convert these images to the same plan to know the coverage of the camera on the plan , each coverage area is composed of multiple triangular planes. The image conversion system and image conversion method shown in the present invention do not need to know any parameters and positions of multiple cameras, and the coverage areas of different lenses do not need to be positioned or corrected. Convert the shooting range of multiple identical or different cameras (that is, a specific area of a complete plane) to the same floor plan, greatly reducing the time spent on manpower when deploying cameras.
此外,處理器將攝像機所拍攝到的範圍自動轉換到平面圖上之後,處理器能夠自動透過影像處理方法追蹤完整平面特定區域中的人體位移,此可以應用到長照中心,由於一般年長者有不習慣配戴電子裝置的特性,藉由本發明所示之影像轉換系統及影像轉換方法,能夠應用完整平面特定區域中標記的中心點位置(即人體位置),以追蹤年長者的移動路徑,有助於判斷年長者是否有失智狀態出現。In addition, after the processor automatically converts the range captured by the camera to the plane map, the processor can automatically track the human body displacement in a specific area of the complete plane through image processing methods. This can be applied to long-term care centers, because the elderly generally have different Due to the habit of wearing electronic devices, the image conversion system and image conversion method shown in the present invention can use the center point position (that is, the position of the human body) marked in the specific area of the complete plane to track the moving path of the elderly, which is helpful It is used to judge whether the elderly have dementia.
本發明之方法,或特定型態或其部份,可以以程式碼的型態存在。程式碼可以包含於實體媒體,如軟碟、光碟片、硬碟、或是任何其他機器可讀取(如電腦可讀取)儲存媒體,亦或不限於外在形式之電腦程式產品,其中,當程式碼被機器,如電腦載入且執行時,此機器變成用以參與本發明之裝置。程式碼也可以透過一些傳送媒體,如電線或電纜、光纖、或是任何傳輸型態進行傳送,其中,當程式碼被機器,如電腦接收、載入且執行時,此機器變成用以參與本發明之裝置。當在一般用途處理單元實作時,程式碼結合處理單元提供一操作類似於應用特定邏輯電路之獨特裝置。The methods of the present invention, or specific forms or parts thereof, may exist in the form of program codes. The code may be contained in a physical medium, such as a floppy disk, compact disc, hard disk, or any other machine-readable (such as computer-readable) storage medium, or a computer program product without limitation in external form, wherein, When the program code is loaded and executed by a machine, such as a computer, the machine becomes a device for participating in the present invention. Code may also be sent via some transmission medium, such as wire or cable, optical fiber, or any type of transmission in which when the code is received, loaded, and executed by a machine, such as a computer, that machine becomes the Invented device. When implemented on a general-purpose processing unit, the code combines with the processing unit to provide a unique device that operates similarly to application-specific logic circuits.
雖然本發明已以實施方式揭露如上,然其並非用以限定本發明,任何熟習此技藝者,在不脫離本發明之精神和範圍內,當可作各種之更動與潤飾,因此本發明之保護範圍當視後附之申請專利範圍所界定者為準。Although the present invention has been disclosed above in terms of implementation, it is not intended to limit the present invention. Anyone skilled in this art can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the protection of the present invention The scope shall be defined by the appended patent application scope.
100:影像轉換系統
10, 12:攝像機
20:處理器
AP1~AP4:基地台
TAG0~TAG3:定位標籤
200:影像轉換系統
300:影像轉換方法
310~330:步驟
SP:空間
TR, TR’, TR’’:三角型平面
F1, F2:框選範圍
P1, P2:中心點位置
OBJ1~OBJ5:物件
Ra: 平面特定區域
700:平面圖
800:移動路徑
L1, L2:移動軌跡
100:
第1圖係依照本發明一實施例繪示影像轉換系統之方塊圖。 第2圖係依照本發明一實施例繪示影像轉換系統之方塊圖。 第3圖係依照本發明一實施例繪示影像轉換方法之示意圖。 第4圖係依照本發明一實施例繪示室內定位方法之示意圖。 第5圖係依照本發明一實施例繪示室內定位方法之示意圖。 第6圖係依照本發明一實施例繪示攝像機擷取之影像之示意圖。 第7圖係依照本發明一實施例繪示平面圖之示意圖。 第8圖係依照本發明一實施例繪示人體的移動路徑之示意圖。 FIG. 1 is a block diagram of an image conversion system according to an embodiment of the present invention. FIG. 2 is a block diagram illustrating an image conversion system according to an embodiment of the present invention. FIG. 3 is a schematic diagram illustrating an image conversion method according to an embodiment of the present invention. FIG. 4 is a schematic diagram illustrating an indoor positioning method according to an embodiment of the present invention. FIG. 5 is a schematic diagram illustrating an indoor positioning method according to an embodiment of the present invention. FIG. 6 is a schematic diagram illustrating an image captured by a camera according to an embodiment of the present invention. Fig. 7 is a schematic diagram showing a plan view according to an embodiment of the present invention. FIG. 8 is a schematic diagram illustrating a moving path of a human body according to an embodiment of the present invention.
300:影像轉換方法 300: Image conversion method
310~330:步驟 310~330: Steps
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