膚色圖 的英文怎麼說

中文拼音 [fūshǎitú]
膚色圖 英文
broca scale
  • 膚 : 名詞（皮膚） skin
  • 色 : 色名詞[口語] （顏色） colour
  • 圖 : Ⅰ名詞1 （繪畫表現出的形象; 圖畫） picture; chart; drawing; map 2 （計劃） plan; scheme; attempt 3...
  • 膚色 : colour of skin; colour; complexion膚色統治 pigmentocracy; 膚色圖 broca scale; 膚色障礙 colour bar
  1. The skin - color difference between the khoisan and bantu speakers such as the zulu indicates that the length of time that a group has inhabited a particular region is important in understanding why they have the color they do

    班圖族群（如祖魯人）與郭依桑人的膚色差異，表示一個族群居住在一特定地區的時間，對了解他們的膚色特徵十分重要。
  2. Firstly, human skin - color information is used to segment images into skin color region and non - skin color region, then pretreat the skin - color region and come into the phase of image similarity

    首先利用彩色圖像的顏色信息把彩色圖像分割成膚色區域與非膚色區域，然後對膚色區域做預處理后，進入圖像似然度檢測階段。
  3. In this paper, we compared 15 3d colorspaces and 15 2d chrominance planes widely used in skin - tone detection in terms of compactness of skin class, discriminability between skin and non - skin classes as well as the classification performance of several detectors based on a data set of 1894 images

    摘要在綜述現存膚色檢測演算法所使用不同顏色空間的基礎上，基於一個含有1894張圖像的樣本庫，採用膚色內聚性和膚色非膚色類可分離性指標以及相應的分類器性能評估準則，考查了包含所有常用顏色空間的15個3維顏色空間和15個2維色度平面，建立了一個完善的膚色空間評價體系。
  4. Based on mean shift algorithm i propose dynamical mean shift algorithm. in this paper, i use dmsa to track face in video sequences which combines a probability distribution image of flesh color. in the end of this paper, dmsa ' s tracking accuracy, tolerance to noise, distractors and performance are studied

    在基於靜態圖像中使用的msa （ meanshiftalgorithm ）演算法的基礎上，本論文提出了dmsa （ dynamicalmeanshiftalgorithm ）跟蹤演算法，並結合膚色概率分佈，將其應用於人臉跟蹤的研究中。
  5. This paper makes a good study of the face recognition, including testifying the face from an image, partitioning main area of the face, abstracting the edge of the image, locating the characteristic points, recognizing the same face, etc. i have many new ideas in the study as follows : a method partitioning facial area from an image by 24 _ bit color is described

    本論文對人臉識別技術的演算法作了全面的研究，包括對圖像進行人臉的檢測、區域分割、邊緣提取、去除噪聲和特徵點的定位、特徵向量的提取、識別等這幾個部分。提出了如下幾種實用和有效的演算法：在對當前多種人臉檢測方法的研究后，提出了一種利用膚色對面部圖像進行分割的方法。
  6. A systematic summary of previous work has been given first. then this paper presents a novel multi - stage face detection algorithm, which makes a good use of human face pattern ' s valuable information in colour image sequences. the difficult detection task has been divided into four steps : the preprocessing, which is to gain skin colored regions with human skin color model ; the roughly detection and face region refining by elliptic curve fitting ; the fine detection with facial features " detection and location ; the face / non - face classification step based on pca and gaussian density estimation technique

    本文對彩色序列圖像中的人臉檢測和跟蹤技術進行了深入的研究，其具體內容為：對近年來的研究工作進行了系統的介紹；提出了一個由粗到細的多階段的人臉檢測演算法，該演算法充分利用了序列圖像中人臉模式的各種有用信息，將復雜的檢測工作分為了四個部分：膚色區域分割預處理，人臉粗檢及利用橢圓擬和的人臉區域提煉，應用人臉基本特徵檢測和定位的人臉細檢， pca結合高斯概率密度估計的人臉驗證。
  7. The templates established for head images of different ages and races are of certain generality, that is, the common templates can be used for decoding head images of the same type

    針對不同年齡段和不同膚色人種的人頭圖象建立的模板具有一定的通用性，也就是說同一類型的人頭圖象解碼時可以採用公共模板。
  8. We will learn how to correct the skin tone, create the transparent wings effect, insert the pictures and transform a simple photo in a mysterious one

    通過這篇即教程我們將學習如何改善人體膚色，如何添加透明的翅膀，插入圖片，如何將一張簡單的圖片神秘化： ）非常有創意的教程~絕對不能錯過哦！
  9. There are three steps of the concrete process of the algorithm : initial localization, separating image and confirmation. firstly, single gaussian model is used to imitate skin - color distribution, meanwhile, skin probability images which is smoothly disposed using middle wave is calculated to attain the initial localization. secondly, in order to separate the latent face region, it uses multimodal information that includes the region growing 、 the hue and brightness 、 skin probability images etc. at last, it adopts the criterion of morphology analysis and face characteristic draw to confirm the latent region

    演算法的具體過程主要分為三個階段:人臉初定位、人臉分割和人臉確認，首先採用高斯模型來模擬膚色分佈並構造出膚色概率圖進行人臉的初定位，並對膚色概率圖採用中值濾波進行平滑處理，接著利用區域生長準則和融合色度、亮度以及膚色概率圖等多源信息相結合的方法對圖像進行分割，以達到分割出潛在臉區的目的，最後採用人臉整體形狀的確認準則和人臉特徵提取的確認準則相結合的方法對潛在臉區的最終確認。
  10. This paper presents a new face detection algorithm for color video images based on skin color and multimodal information fusion. first, this paper presents a new means for selecting skin samples ; and then comparing skin distribution in the eight color spaces and analyzing the adaptability for different skin patterns, poses a face initial orientation ' s method which uses the single gaussian model in the tsl color spaces, and calculates skin probability images ; afterwards comprehensive comparing three typical threshold value separating algorithms, put forwards a face separating method which bases on region growing and fuses multimodal informations ; final, raises a face confirming algorithm which fuses three shape features

    首先提出了?種新的膚色樣本選取方法；然後通過對八種色空間膚色分佈的比較以及不同膚色模型適應性的分析，提出了在tsl色空間上用單峰高斯模型模擬膚色分佈，求得膚色概率圖進行人臉初定位的方法；隨后在綜合比較三個典型閾值化分割演算法的基礎上，提出了融合多源信息進行區域生長分割人臉的演算法；最後提出了融合三個形狀特徵的人臉確認演算法。
  11. In geometry fitting, we introduce the scattered data interpolation technology, and by using the corresponding points on the shared boundary between the given facial mesh and the organ to be pasted, the facial mesh can be automatically fitted to the organ to be used. and in texture fitting, we extend the improved field - based morphing algorithm to the corresponding texture map, and with the preprocessing of the histogram - matching method we can obtain smooth replacing result in the texture map

    在紋理上，將改進的場變形演算法拓展到人臉模型對應的紋理圖上，不但完成了紋理圖中對應器官區域的替換，同時通過引入以點到邊界距離的函數為權重的線性插值，實現了在替換器官區域從目標圖像到源圖像的均勻過渡；又通過引入直方圖規定化的技術，解決了由於膚色相差較大而產生的邊界不能平滑過渡的問題。
  12. Nevertheless, it ' s not very precise to locate the skin color region only in this way. so the texture model is introduced into the system. consequently, we get the skin region by the combination of skin color model and texture color model

    然而，單純地使用膚色模型並不能準確的找出皮膚區域，觀察發現皮膚區域多為光滑的連通區域，因此在上一步工作的基礎上作者引入了紋理模型對原圖像進一步的處理產生標注皮膚區域的掩碼圖像。
  13. Cl : you are painting a picture of an israeli government, with the support of a substantial part of its jewish population, which aims toward permanent subordination of palestinian arabs within its borders, along with domination over something that might be called a palestinian state but what would really amount to a dependent bantustan

    膚色線:你所繪畫的以色列政府，由相當一部份的猶太人口支持，試圖達到永久性地奴役在境內的巴勒斯坦阿拉伯人和控制一個或者可以稱為巴勒斯坦國但實際上是一個依賴性的班圖斯坦
  14. At the left, dark vulvar skin leads to vagina and to cervix in the center, where an irregular tan tumor mass is seen infiltrating upward to the bladder

    圖左示外陰（皮膚色深） 、陰道，圖中示宮頸腫瘤，一不規則褐色腫物，向下浸潤至膀胱。
  15. Lipstick colour - should be in the hue of red. dark brown, skin colours, pastel colours and shocking pink should be avoided. lip liner should match the colour of the lipstick

    請使用正統紅色的唇膏（如圖示） ，勿著深咖啡色、淺膚色或熒光粉色。唇線與唇膏的色調應一致。
  16. A binary skin color map is firstly obtained by applying the skin / non - skin classification algorithm, and then the integral image representation is used to preprocess the skin and intensity map

    首先採用基於膚色模型的膚色歸類器生成膚色二值圖，然後利用整形圖技術對膚色和灰度分割圖進行預計算。
  17. In general, three main steps can be distinguished in tackling the problem. first, before a facial expression can be analyzed, the face must be detected in a scene. based on color transformation and a novel lighting compensation technique, skin regions can be detected over the entire image ; then eye and mouth maps are constructed for verifying each face candidates

    所提出的人臉表情的自動識別方法主要分為三步，首先是人臉檢測，文中提出了一種基於色彩空間轉換和亮度補償的膚色檢測演算法，然後通過構建眼，嘴模板來進行人臉的特徵點定位，以及獲得圖像中人臉所在區域。
  18. In this paper we studied and compared general face detecting algorithms. in allusion to the characteristics that image of video sequences has low resolution ratio and large quantity of color information ; we propose a face detecting method based on skin color and local human face structural feature

    本文對在靜態圖像和視頻圖像序列中常用的人臉檢測演算法進行了研究和比較，針對數字視頻中圖像解析度較低，包含大量色彩信息的特點我們提出了一種基於膚色和人臉局部特徵的檢測方法。
  19. In order to solve the multiple camera best view selection problems, not only we present two selection algorithms based on skin ratio and color hist matching, but an improved face detection algorithm based on motion segmentation is presented for static camera

    提出了一種基於多攝像機的動態背景下人臉最優視角選擇演算法。在給出最優視角選擇準則的基礎上，根據實際應用分別提出基於膚色比率與彩色直方圖的最優視角選擇演算法。
  20. In this paper, we present a multi - feature optimal fusion algorithm, inclusive of skin color, to detect one or multiple faces in color image with complex background. it is a hierarchical approach and integrates the skin color segmentation, face template matching and a neural network frontal face detector. with the elimination of false areas, the search area will become smaller and smaller, and the detection will be accomplished eventually

    該演算法是一種層次式、由粗到精的檢測方法，按照「分割-搜索」的檢測模式，將膚色分割、平均臉模板匹配與神經網路驗證結合起來，採取逐步排除的方法，一步一步縮小搜索區域，實現彩色圖像中單個或多個正面端正人臉的檢測與定位。
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