| Recovering Consistent Video Depth Maps via Bundle Optimization (2009) | |||||||||||||||
Abstract | |||||||||||||||
| input sequence output video depth maps Figure 1. High-quality depth reconstruction from the video sequence “Road ” containing complex occlusions. Left: An input video sequence taken by a moving camera. Right: Video depth maps automatically computed by our method. The thin posts of the traffic sign and street lamp, as well as the road with graduate depth change, are accurately constructed in the recovered depth maps. This paper presents a novel method for reconstructing high-quality video depth maps. A bundle optimization model is proposed to address the key issues, including image noise and occlusions, in stereo reconstruction. Our method not only uses the color constancy constraint, but also explicitly incorporates the geometric coherence constraint associating multiple frames in a video, thus can naturally maintain the temporal coherence of the recovered video depths without introducing over-smoothing artifact. To make the inference problem tractable, we introduce an iterative optimization scheme by first initializing disparity maps using segmentation prior and then refining the disparities by means of bundle optimization. Unlike previous work estimating complex visibility parameters, our approach implicitly models the probabilistic visibility in a statistical way. The effectiveness of our automatic method is demonstrated using challenging video examples. 1. | |||||||||||||||
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