...
首页> 外文期刊>Oriental journal of computer science and technology >Real Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Images
【24h】

Real Time Depth Hole Filling using Kinect Sensor and Depth Extract from Stereo Images

机译:使用Kinect Sensor和STEREO图像深度提取物的实时深度孔填充

获取原文
   

获取外文期刊封面封底 >>

       

摘要

The researcher have suggested real time depth based on frequency domain hole filling. It get better quality of depth sequence generated by sensor. This method is capable to produce high feature depth video which can be quite useful in improving the performance of various applications of Microsoft Kinect such as obstacle detection and avoidance, facial tracking, gesture recognition, pose estimation and skeletal. For stereo matching approach images depth extraction is the hybrid (Combination of Morphological Operation) mathematical algorithm. There are few step like color conversion, block matching, guided filtering, minimum disparity assignment design, mathematical perimeter, zero depth assignment, combination of hole filling and permutation of morphological operator and last nonlinear spatial filtering. Our algorithm is produce smooth, reliable, noise less and efficient depth map. The evaluation parameter such as Structure Similarity Index Map (SSIM), Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) measure the results for proportional analysis.
机译:研究人员建议基于频域孔填充的实时深度。它得到了传感器产生的更好的深度序列质量。该方法能够产生高特征深度视频,这对于提高Microsoft Kinect的各种应用的性能非常有用,例如障碍物检测和避免,面部跟踪,手势识别,姿势估计和骨骼。对于立体声匹配方法,图像深度提取是混合(形态学操作的组合)数学算法。几乎没有步骤类似的颜色转换,块匹配,引导滤波,最小差异分配设计,数学外围,零深度分配,孔填充和形态算子的漏洞组合和最后的非线性空间滤波。我们的算法产生光滑,可靠,噪音较少,噪声较差和高效的深度图。评估参数如结构相似性索引图(SSIM),峰值信号到噪声比(PSNR)和均方误差(MSE)测量比例分析的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号