previous frame造句
例句與造句
- We detect stack overflow by monitoring the previous frame pointer . such comes the tool fpw ( frame pointer watcher )
作者提出利用前幀指針檢測堆棧溢出的方法即fpw ( framepointerwatcher ) 。 - Frame # 6 : the vigor of the right arm pull is evidenced by the amount of upper arm adduction that has occurred since the previous frame
畫面6 ：從上幀畫面開始的上臂內(nèi)收繼續(xù)加大，這也使得右臂的劃水力增大。 - In this case , we will simply determine the coordinates of a cell of pixels closest to the top of the captured image and that changed from the previous frame
在這個示例中，我們只判斷最接近捕捉的圖像頂部與前一幀相比有變化的像素的坐標(biāo)。 - The sum of square differences ( ssd ) , which has been defined as square summation of corresponding pixel differences between current and previous frame , has been endowed a novel connotation in this paper
本文賦予當(dāng)前幀總方差ssd新內(nèi)涵,定義其為當(dāng)前幀與前一幀對應(yīng)像素差的平方和。 - It uses different zones named usu - prefrm zone and jmp - prefrm zone to record changing of the previous frame pointer in stack . compared with stack guard and rad , fpw has more efficent performance , same safety and less memory cost
與stackguard和rad相比， fpw具有同樣程度的安全性、占用更少的內(nèi)存空間、減少進(jìn)程意外終止的可能性和更好的運(yùn)行效果等優(yōu)點(diǎn)。 - It's difficult to find previous frame in a sentence. 用previous frame造句挺難的
- Also an algorithm which combines both model matching and feature matching is put forward . the algorithm uses the object contour in previous frame as the reference template of current frame . based on the fact that object has a continuous track in movement , object ’ s current position can be predicted based on previous position and then match the reference template around the predicted position
該算法將前一幀目標(biāo)輪廓作為當(dāng)前幀的參考模板,根據(jù)目標(biāo)在運(yùn)動過程中具有軌跡連續(xù)性的特點(diǎn),利用目標(biāo)過去的跟蹤點(diǎn)位置信息得到當(dāng)前的預(yù)測位置點(diǎn),然后在預(yù)測位置點(diǎn)周圍一定范圍內(nèi)進(jìn)行模型匹配,以與參考模板匹配值最大的輪廓作為當(dāng)前幀的目標(biāo)輪廓,并且把它更新作為下一幀的參考模板。 - Users plot a coarse outline of video objects in the graphic user interface ( gui ) using the mouse at the first step , then fill the outline to obtain a binary model , using seed growing and wavelet edge correct the outline . in tracking video objects , we obtain an initial segmentation uses motion information and the model of previous frame , and correct by the information of space . finally , we obtain an accurate segmentation
利用視覺系統(tǒng)的周邊抑制機(jī)制對模板外的象素進(jìn)行屏蔽，消除背景影響，由自動閾值選取的小波邊緣提取獲得視頻對象的邊界，利用種子生長法進(jìn)行輪廓擬合，由最短路徑法校正模板，在進(jìn)行視頻對象的跟蹤時，利用運(yùn)動信息和上一幀的模板，得到一個初始分割，利用空間信息對邊界象素調(diào)整，最后得到精確分割的視頻對象。 - On the basis of this introduction , some part of algorithm is improved . it includes : a new bit - allocation algorithm based on linear predication , that is to predicate the initial value used in bit - allocation procedure by the initial value of previous frame according to the correlation of the previous frame and the current frame . so the iterated loop number is reduced and the complexity of audio coding is reduced
其中的一些主要改進(jìn)有：提出一種基于線性預(yù)測的比特分配算法，即利用幀與幀之間存在的相關(guān)性，根據(jù)前幾幀的比特分配信息初值預(yù)測出當(dāng)前幀的比特分配信息初值，通過合理設(shè)定比特分配信息初值，使得比特分配的迭代次數(shù)減少，從而節(jié)省了音頻編碼的運(yùn)算量。