CAJ | 학술논문

时域相关性在视频分析中具有重要作用，但在估算光流时，这一特性却很少被应用。针对这一情况，提出在H-S光流模型基础上引入前向帧，并加入光流时域上的相关性约束构造出一种多帧光流模型以提高光流估算精度。同时，针对光流非线性能量泛函求解异常复杂的情况，提出运用迭代重加权最小二乘法（IRLS）简化模型线性化求解过程。最后，结合所得光流给出一种改进的车辆检测跟踪方案，通过先估算光流后帧差提取，可得到更加精确的车辆运动信息并可避免多个车辆的光流域连接成块。实验结果表明，IRLS法简化求解的多帧模型可同时估算出多个帧间光流并能显著提高光流估算精度，基于此多帧光流的车辆检测跟踪方案的车辆跟踪成功率在86％以上，达到了预期要求。
시역상관성재시빈분석중구유중요작용，단재고산광류시，저일특성각흔소피응용。침대저일정황，제출재H-S광류모형기출상인입전향정，병가입광류시역상적상관성약속구조출일충다정광류모형이제고광류고산정도。동시，침대광류비선성능량범함구해이상복잡적정황，제출운용질대중가권최소이승법（IRLS）간화모형선성화구해과정。최후，결합소득광류급출일충개진적차량검측근종방안，통과선고산광류후정차제취，가득도경가정학적차량운동신식병가피면다개차량적광류역련접성괴。실험결과표명，IRLS법간화구해적다정모형가동시고산출다개정간광류병능현저제고광류고산정도，기우차다정광류적차량검측근종방안적차량근종성공솔재86％이상，체도료예기요구。
Despite the fact that time domain correlation plays an important role in analysing video data,this characteristic has hardly been exploited in optical flow estimation.In light of this,we presented to construct a multi-frame optical flow model by introducing the forward frame based on H-S optical flow model and adding the time domain correlation constraint for improving the precision of optical flow estimation. Meanwhile,aiming at the case that it is extremely complicated in solving the nonlinear energy functional of optical flow,we proposed to use the method of iterative reweighted least squares (IRLS)to simplify the process of linearised model solution.At last,in combination with the optical flow derived we offered an improved vehicle detection and tracking scheme.By executing the differential extraction after the optical flow estimation is completed,the scheme could get more accurate vehicle motion information and prevent the problem that the optical flow areas of vehicles may connect to a block.Experimental results showed that the simplified solution of multi-frame model by IRLS can estimate simultaneously multiple inter-frame optical flows and significantly improve the estimation precision,the vehicle detection and tracking scheme based on this multi-frame optical flow reached over 86% tracking success rate and achieved the expected demand as well.