In order to get the moving vehicle detection, vehicle occlusion detection is as an essential link.
为了更好进行运动车辆检测，遮挡检测成为一个必不可少的环节。
In processing the dynamic images, occlusion detection and tracking of moving targets in an image sequence are very significant and difficult problems.
图像序列中运动目标的遮挡检测和处理是目前在动态图像处理时经常碰到，且比较难于解决的问题。
The key techniques include disparity 'estimation, occlusion detection, disparity compensated difference coding and joint estimation of disparity and motion.
核心技术有视差估计、遮挡检测、立体残差图像编码、运动和视差的联合估计等。
Experimental results show that the new algorithm has certain enhancement in the precision of occlusion detection and matching, and is more reliable and faster than conventional dynamic algorithms.
实验结果表明，新算法比传统的动态规划算法在遮挡检测和匹配精度上都有一定的提高，算法可靠性强，运算量小。
This paper proposes a novel cooperative algorithm for disparity estimation and occlusion points detection, which is adaptive to stereo image coding.
本文提出一种新的用于立体图像编码的视差估计和遮挡点检测混合算法。
We dedicated to the research of it. In order to improve its performance, we worked on the selection and training process of classifier, occlusion handling, multiple detection results merging.
本文在对该方法进行研究的基础上，为了提高检测的性能，对分类器的选取、训练方法、遮挡处理、结果融合等方面进行了研究。
But the vehicle occlusion occurred during detection seriously affect the vehicle's statistics.
但是检测过程中发生的车辆遮挡严重影响了车辆的统计。
The experimental results demonstrate that the algorithm can further improve the multi-pose face detection accuracy and is highly robust to lighting condition, facial expression and occlusion.
对比实验表明，算法提高了多姿态人脸的检测率，对光照、表情和遮挡有较强的鲁棒性。
At the same time, since the human face detection can be greatly influenced by background, light, gesture, expression, occlusion, noise and so on, it also became a much complicated topic.
同时，由于人脸检测受背景、光照、姿态、表情、遮挡、噪声等影响较大，也成为一个较为复杂的课题。
At the same time, since the human face detection can be greatly influenced by background, light, gesture, expression, occlusion, noise and so on, it also became a much complicated topic.
同时，由于人脸检测受背景、光照、姿态、表情、遮挡、噪声等影响较大，也成为一个较为复杂的课题。
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