Hyun Sung Chang

3D Display Calibration by Visual Pattern Analysis

Nearly all 3D displays need calibration for correct rendering. More often than not, the optical elements in a 3D display are misaligned from the designed parameter setting. As a result, 3D magic does not perform well as intended. The observed images tend to get distorted. In this paper, we propose a novel display calibration method to fix the situation. In our method, a pattern image is displayed on the panel and a camera takes its pictures twice at different positions. Then, based on a quantitative model, we extract all display parameters (i.e., pitch, slanted angle, gap or thickness, and offset) from the observed patterns in the captured images. For high accuracy and robustness, our method analyzes the patterns mostly in the frequency domain. We conduct two types of experiments for validation; one with optical simulation for quantitative results and the other with real-life displays for qualitative assessment. Experimental results demonstrate that our method is quite accurate, about a half order of magnitude higher than prior work; is efficient, spending less than 2s for computation; and is robust to noise, working well in the SNR regime as low as 6dB.

Local deformation calibration for autostereoscopic 3D display

Calibration is vital to autostereoscopic 3D displays. This paper proposes a local calibration method that copes with any type of deformation in the optical layer. The proposed method is based on visual pattern analysis. Given the observations, we manage to localize the optical slits by matching the observations to the input pattern. In a principled optimization framework, we find an efficient calibration algorithm. Experimental validation follows. The local calibration shows significant improvement in 3D visual quality over the global calibration method. This paper also finds a new intuitive insight on the calibration in terms of the light field theory.

Yet Another Cost Aggregation Over Models

In the recent decades, we have witnessed the advent of local or non-local filters for cost aggregation in stereo matching, pushing the envelope of local methods to the degree of global methods, while maintaining the efficiency. A specific filter with a specific parameter setting may have a potential to best work for an image pair, but may not guarantee equally good performance for other image pairs. To address this problem, we propose a mixture-of-experts model, which applies a heterogeneous set of filters on the cost volume and adaptively combines the results. We employ supervised learning to estimate per-pixel mixing coefficients, which are used to adaptively control the weight of the filter responses. Through experiments, we show that the mixture model significantly reduces errors in disparity estimation and even outperforms the strategy of selecting the best per-pixel filter from the pool of filters in the average sense.

Analysis of radial symmetric interpolation in hologram generation

We present an analysis of quality degradation sources in radial symmetric interpolation method which exploits concentric redundancy of point hologram pattern to reduce computational complexity in hologram pattern generation. In this method, the wave information of diagonal line is periodically sampled and point hologram is calculated by linear interpolation. During this sampling and interpolation process, the wave information can be modified from the original signal and degrade the reconstruction quality compared to analytic pattern calculation method. The effect of sampling and linear interpolation is investigated in spatial and frequency domains.

Uncalibrated multiview synthesis

Abstract. Nonideal stereo videos do not hinder viewing experience in stereoscopic displays. However, for autostereoscopic displays nonideal stereo videos are the main cause of reduced three-dimensional quality causing calibration artifacts and multiview synthesis artifacts. We propose an efficient multiview rendering algorithm for autostereoscopic displays that takes uncalibrated stereo as input. First, the epipolar geometry of multiple viewpoints is analyzed for multiview displays. The uncalibrated camera poses for multiview display viewpoints are then estimated by algebraic approximation. The multiview images of the approximated uncalibrated camera poses do not contain any projection or warping distortion. Finally, by the exploiting rectification homographies and disparities of rectified stereo, one can determine the multiview images with their estimated camera poses. The experimental results show that the multiview synthesis algorithm can provide results that are both temporally consistent and well-calibrated without warping distortion.