幀間距 的英文怎麼說
中文拼音 [zhèngjiānjù]
幀間距
英文
frame pitch-
Because the air - borne imaging system is required a far acting distance and the focal length of its optical system is long. influenced by the unsteady or moving platform mounted on plane, the change between the frames of image sequence is more. problems of image fuzziness and instability tend to be striking out, which becomes a bottleneck restricting the air - borne reconnaissance, collimation, evaluating beat effect
機載光電成像系統，由於要求作用距離遠，故其光學系統焦距長，受其載體姿態變化和振動的影響，圖像序列幀間變化過大，造成觀察者覺得模糊、不穩定，己成為制約空中偵察、瞄準、打擊效果評估等功能的瓶頸。According to the characteristic of ieee 1394 with wide bandwidth, common and real - time, the author put forward ieee 13 94 should be applied into real - time digital video transfer in optics - electronics theodolite. before engineering realization, carried out a video image transfer test on three types of digital video tape recorders and camera with ieee 1394 interface. we found that digital videos without compression transfered under ieee 1394 standard ( transfer from 4. 5m to 100m ), compared with analog videos, have no geometric distortion, and have better luminance, contrast, definition
作為工程實現前的實驗研究，對三類具有ieee1394介面的數字錄像機和攝像機進行了視頻圖像傳輸實驗，發現無壓縮格式的按ieee1394標準傳輸的數字視頻圖像（傳輸距離從4 . 5米到100米之間） ，較原始模擬視頻圖像在幾何位置信息上沒有衰變，而在亮度、對比度、邊緣清晰度這些方面有明顯的優勢；但是按dvcam壓縮格式（常見于sony公司的系列產品，是5 ： 1的dct幀內壓縮）壓縮的數字視頻圖像，較原始模擬參照圖像有明顯的幾何畸變。The algorithm can be finished with automating in most case and suits for any scale image with unknown any parameter of camera. mosaic image is smooth and has no gap. 2
分析表明，本演算法適宜於任何大小的圖象並且不需要知道相機的任何參數（如焦距） ，對相鄰幀圖象之間相機的運動沒有嚴格的限制。The calculation formula of micropiv technique is the original definition of velocity : v = [ s ( t2 ) - s ( tl ) ] / ( t2 - tl ). on the two neighboring frame of images, we search for the two small areas which have the largest correlation. by dividing their distance by their shooting interval, we got the average velocity of this small area in this interval, and then got the velocity of full flow
Piv測試原理的計算公式，是速度的原始定義： v = [ s （ t _ 2 ） - s （ t _ 1 ） ] （ t _ 2 - t _ 1 ） 。在相鄰兩幀圖像上，找出相關度最大的兩個小區域，用它們之間的距離除以兩次拍攝之間的時間間隔，就得到這個小區域在間隔時間內的平均速度，進而得到整個流場的速度分佈。Following are detailed steps of this system : in the segmentation section, we use three successive frames to detect the motion infomation of the pictures, by using blockmatching algorithm in two successive frames twice, we can get two pictures composed of motion blocks of the moving object, then we find out the common motion blocks of the two pictures, experiments prove these blocks approximately compose the moving object. after getting the motion blocks, we calculate the center of these blocks as the center of the moving object, thus we can use the center point as the origin, construct n straight linesjoining the boundry of the image and the center. on each line, we can find out a proper point near the object contour according to some criteria, then we use these n points as the initial points of the snake and let the snake converge on the object contour, thus finish the segmentation of the moving object
本方案的實現過程為：分割部分：對運動目標的前後三幀進行兩次塊匹配運動檢測，通過找出兩個匹配結果中運動圖像塊的公共部分，獲得組成運動目標的圖像塊；求出運動目標圖像塊的形心作為運動目標的中心，以此中心為端點，向四周發散出角度間隔為的n條射線，射線的另一端終止於圖像的邊緣；在每條射線上按照一定的準則（點的梯度和與目標中心的距離在一定閾值范圍內）找出n個初始輪廓點；以這些初始輪廓點作為主動輪廓模型（ snake ）的初始點，用改進的貪婪演算法使snake收斂到待分割的運動目標輪廓上。The necessity and possibility to estimate and compensate camera rotation in the long focus imaging system is proposed according to characteristics of airborne imaging system. and choosing some points that have great gray levels as image characteristic to estimate motion is also given
針對機載成像的特點，提出了長焦距攝像系統檢測和補償旋轉運動的必要與可能性以及利用選擇特徵圖像中的最大灰度值點，作為圖像特徵來估計圖像序列幀間運動的方法。In temporal segmentation a statistical model is used to automatically separate the moving areas from the background in a general video sequence. the spatial segmentation bases on the results of temporal segmentation and using region - growing algorithm in rgb space can locate precise boundary of moving object. lastly, using segment moving object as the initial model, moving object can be tracked by matching an image to a model based on hausdorff distance on a sequence of video, and the model is updated every frame to accommodate for changes in shape
時間分割中採用連續幀間差的統計假設檢驗，確定運動對象的位置，自動地分離出運動區域與背景區域；空間分割中則採用基於顏色的區域增長演算法來精確地提取運動對象的輪廓；最後，將提取到的運動對象作為模板，對后續的視頻序列，用基於hausdorff距離度量匹配，來跟蹤並提取后續幀中運動對象。分享友人