Recent autostereoscopic 3-D (A3D) displays suffer from many limitations such as narrow viewing angle, low resolution, and shallow depth effects. As these limitations mainly originate from the insufficiency of pixel resources, it is not easy to obtain a feasible solution that can solve all the limitations simultaneously. In many cases, it will be better to find a good compromising design. Generally, the multiview display and the integral imaging display are the representative designs of A3D. However, as they are too canonical and lack flexibility in design, they tend to be a tradeoff. To address these design issues, we have analyzed the multiview display and the integral image display in a light-field coordinate and developed a 3-D display design framework in a light-field space. The developed framework does not use the “view” concept anymore. Instead, it considers the spatial distribution of rays of the 3-D display and provides more flexible and sophisticated design methods. In this paper, the developed design method is explained using a new pixel value assigning algorithm, called the light-field rendering, and vision-based parameter calibration methods for 3-D displays. We have also analyzed the blur effects caused by the depth and display characteristics. By implementing the proposed method, we have designed a 65-in 96-view display with a 4K panel. The developed prototype has showed almost seamless parallax with a high-resolution comparable to the conventional four to five views displays. This paper will be useful to readers interested in A3D displays, especially in the multiview and the integral imaging displays.

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.

Saliency detection for images and videos has become increasingly popular due to its wide applicability. In this paper, we propose a novel bottom-up video saliency extraction method, which includes two parts: static saliency detection and dynamic saliency detection. Firstly, we consider the static saliency detection as a classification problem: a scene can be divided to saliency region and non-saliency region. To solve such problem, we use a frequency-based sampling method and then introduce a Canonical Correlation Analysis (CCA)-based classification strategy using multiple cues. Secondly, we combine motion feature with the spatial feature to represent dynamic saliency in temporal domain. We test our method in both image based saliency extraction and video saliency extraction. The results illustrate its high performance in both two tasks.

In this paper, we propose a precise and fast eye center localization method. The method is based on SDM [1] algorithm, which has achieved impressive performance in face alignment area. In this work, we further improve the basic SDM algorithm in two aspects: 1) employ the coarse to fine strategy to enhance the robustness to initialization; 2) utilize multiple nonlinear features to ensure the robustness while improve the accuracy. Experimental results on BioID database shows that our improved SDM achieves preferable localization accuracy against the state-of-the-art methods at a speed as fast as 2ms to locate two eyes.

Existing appearance-based gaze estimation methods suffer from tedious calibration and appearance variation caused by head movement. In this paper, to handle this problem, we propose a novel appearance-based gaze estimation method by introducing supervised adaptive feature extraction and hierarchical mapping model. Firstly, an adaptive feature learning method is proposed to extract topology-preserving (TOP) feature individually. Then hierarchical mapping method is proposed to localize gaze position based on coarse-to-fine strategy. Appearance synthesis approach is used to increase the refer sample density. Experiments show that under the condition of sparse calibration, proposed method has better performance in accuracy than existing methods under fixed head pose without chinrest. Moreover, our method can be easily extended for head pose-varying gaze estimation.

This paper presents an application of evolutionary programming to parameter optimization in the design of a voltage reference circuit. Designing circuits consists of two steps: topological design and parameter determination. After designing a topology suitable for the circuit, the designer selects an appropriate value for each circuit element from a circuit analysis and his experience. This step is difficult and time consuming because the designer must consider many factors simultaneously. As more precise circuits are required, parameter optimization becomes more complex. The voltage reference circuit, which requires a precise reference voltage independent of power fluctuation and temperature change, is such an example. In this paper, evolutionary programming is used as an effective method of finding good parameter values for the elements of the voltage reference circuit. Simulation results show that this method provides good performance and can be used as an effective method for circuit design.