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The present decade has seen the growth of both, the software and hardware for three dimensional televisions in real time applications. Depth map is fundamental key of 3-Dimensional algorithms. Reliable depth map is an acceptance in 3D transmission, analysis and compression of algorithm. Computer vision and pattern recognition research fields use sensor like low cost Microsoft kinect. Kinect sensor suffers from some problems of noise, poor accuracy and unmatched edges. This paper presents effective solution to improve the real time depth sequences and real time 3-D map using warping method from kinect sensor. We proposed real time frequency domain based depth data refurbishment and improve the quality of depth video provided by sensors‘ Microsoft Kinect. The quality of the depth map is improved by depth refurbishment in frequency domain technique, filling the holes present in the maps, 2-Dimensional spatial filtering and permutation of morphological operation. We show that the proposed approach is able to generate high quality depth maps which can be quite useful in improving the performance of various applications of Microsoft Kinect such as obstacle detection and avoidance, pose estimation, gesture recognition, skeletal and facial tracking, etc. We produce the real time 3-D map using warping method. An experimental result shows that the quality of our proposed method is better than previous research works. Our algorithm produces noise less, reliable, smooth and efficient depth sequence. The qualitative parameter Peak Signal to Noise Ratio (PSNR), Structure Similarity Index Map (SSIM) and Mean Square Error (MSE) measure the real time results for comparative analysis.

Real Time Depth Data Refurbishment in Frequency Domain and 3D Modeling Map Using Microsoft Kinect Sensor