最後取樣單位 的英文怎麼說
中文拼音 [zuìhòuqǔyàngdānwèi]
最後取樣單位
英文
ultimate sampling unit- 最 : 副詞(表示某種屬性超過所有同類的人或事物) most; best; worst; first; very; least; above all; -est
- 取 : Ⅰ動詞1 (拿到身邊) take; get; fetch 2 (得到; 招致) aim at; seek 3 (採取; 選取) adopt; assume...
- 樣 : Ⅰ名詞1. (形狀) appearance; shape 2. (樣品) sample; model; pattern Ⅱ量詞(表示事物的種類) kind; type
- 位 : Ⅰ名詞1 (所在或所佔的地方) place; location 2 (職位; 地位) position; post; status 3 (特指皇帝...
- 最後 : last; final; ultimate
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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。Abstract : to settle the numbers of groups, the moth and features of group sampling are analysed, and its estimator is goven. then using cauchyschwartz unequility, it seeks the best apportion with finite cost
文摘:為了確定分類抽樣的各類單位數,分析了分類抽樣的抽取方法和特點,同時給出其簡單估計,然後利用柯西-施瓦茨不等式推導出在給定調查費用情況下的最優分配In order to further video analysis, an algorithm of abrupt shot boundary detection based on fuzzy clustering neural network ( fcnn ) is proposed, and it has the advantages of high precision as well as robust to fast move. caption segmentation is the key to the whole process, fcnn can also be utilized to locate caption region, however, the technique is time - consuming. thus an improved projection segmentation method is presented, and the experimental results show that it is simple and practical, and fits for real - time processing
為了便於后續的視頻分析,提出了一種基於模糊聚類神經網路( fcnn )的鏡頭突變檢測演算法,實現視頻鏡頭分割,該演算法具有檢測精度高、對運動穩健等優點;區域定位是字幕提取的關鍵一環,同樣利用fcnn分類器可實現字幕定位,但其運算量大,定位精度不高,因此提出了一種改進的投影分割方法實現字幕區域定位分割,實驗表明其簡單實用,適于實時處理;考慮到單個字元背景相對簡單,為此提出了一種基於單字元的字幕二值化演算法,最終在經由字元分割、二值化及殘留背景像素清除之後,得到了清晰、高質的字幕圖像,字元識別結果證明了這一點。
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