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This paper presents a hybrid camera system that combines a high-resolution color camera with a low-resolution depth camera to generate high-quality high-resolution depth images. The proposed depth processing algorithm includes depth acquisition, preliminary depth image generation, depth map refinement, and virtual view synthesis. Experimental results show the effectiveness of the system.
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ICPR/WDIA-2012 High Quality Novel View Synthesis Based on Low Resolution Depth Image and High Resolution Color Image Jui-Chiu Chiang, Zheng-Feng Liu, and Wen-Nung Lie National Chung Cheng University Taiwan
Outline • Introduction • Our hybrid camera system • The proposed depth processing algorithm • Experimental results • Conclusion
Color + Depth in 3DTV/FTV • Depth image, in combination with DIBR (Depth Image-Based Rendering) technique, is important in multi-view 3DTV/FTV applications. Depth image Colorimage DIBR view9 view8 view7 view6 view5 view4 view3 view2 view1
Depth acquisition • From stereo matching via disparity estimation • Unreliable for textureless regions • Computationally intensive • From active photo-electrical sensing • Lower resolution • Higher acquisition speed and accuracy Kinect SR4000 ToF
Hybrid camera systems • High-resolution color cameras + Low-resolution depth camera (mis-alignment between their optical axis) • [12]: Use warped data of depth camera to refine ROI disparity of the dual-eye camera • Proposed: one color image is used to refine the warped (to both sides) and up-sampled depth images
Generation of preliminary high-resolution depth image • Purpose: to generate high-resolution depth image at the left and right sides Calibrated camera parameters
Pre-processing of the depth map • 33 median filter • Low resolution to high resolution depth warping • Forward warping with a block size of 55 pixels • Post-processing by morphological operation • Morphological opening
Generation of high quality high-resolution depth image • Color-image-guided depth map refinement
Binarizing the warped depth image to have foreground/background classification • Color segmentation by mean-shift algorithm • Label each segment as FG or BG • Refine the corresponding depth values according to the segment categorization • Bilateral filtering is performed for the edge parts of the modified depth image
Experiments – system configurations • Color image: 640x480 • Depth image: 176x144 (SR4000) • Intel Core 2 Duo Q6600 2.33 GHz, and DDR2 800 4GB
Preliminary high-resolution depth image After depth warping Traditional depth warping After morphological operation
High-quality high-resolution depth image After correction Mean-shift Incorrect pixels Bilateral filtering
Virtual view synthesis based on various depth maps Hole filled Bilateral filtering on edges Bilateral filtering on edges + Gaussian Bilateral filtering
Conclusion • A hybrid camera system consisting of high-resolution color camera and low-resolution depth camera is proposed • A high-quality high-resolution depth images can be obtained for the left and right eyes – multi-view video plus depth (N=2 channels). • Future work • Combine Kinect device and stereo camera to get better depth image and cheaper cost