Several approaches for increasing the speed in computation of the digital holograms of three-dimensional objects have been presented with applications to real-time display of holographic images. Among them, a look-up table (LUT) approach, in which the precalculated principal fringe patterns for all possible image points of the object are provided, has gained a large speed increase in generation of computer-generated holograms. But the greatest drawback of this method is the enormous memory size of the LUT. A novel approach to dramatically reduce the size of the conventional LUT, still keeping its advantage of fast computational speed, is proposed, which is called here a novel LUT (N-LUT) method. A three-dimensional object can be treated as a set of image planes discretely sliced in the z direction, in which each image plane having a fixed depth is approximated as some collection of self-luminous object points of light. In the proposed method, only the fringe patterns of the center points on each image plane are precalculated, called principal fringe patterns (PFPs) and stored in the LUT. Then, the fringe patterns for other object points on each image plane can be obtained by simply shifting this precalculated PFP according to the displaced values from the center to those points and adding them together. Some experimental results reveal that the computational speed and the required memory size of the proposed approach are found to be 69.5 times faster than that of the ray-tracing method and 744 times smaller than that of the conventional LUT method, respectively.

We propose a novel approach to massively reduce the memory of the novel look-up table (N-LUT) for computer-generated holograms by employing one-dimensional (1-D) sub-principle fringe patterns (sub-PFPs). Two-dimensional (2-D) PFPs used in the conventional N-LUT method are decomposed into a pair of 1-D sub-PFPs through a trigonometric relation. Then, these 1-D sub-PFPs are pre-calculated and stored in the proposed method, which results in a remarkable reduction of the memory of the N-LUT. Experimental results reveal that the memory capacity of the LUT, N-LUT and proposed methods have been calculated to be 149.01 TB, 2.29 GB and 1.51 MB, respectively for the 3-D object having image points of 500 × 500 × 256, which means the memory of the proposed method could be reduced by 103 × 10⁶ fold and 1.55 × 10³ fold compared to those of the conventional LUT and N-LUT methods, respectively.

A novel directional backlight system based on volume-holographic optical elements (VHOEs) is demonstrated for time-sequential autostereoscopic three-dimensional (3-D) flat-panel displays. Here, VHOEs are employed to control the direction of light for a time-multiplexed display for each of the left and the right view. Those VHOEs are fabricated by recording interference patterns between collimated reference beams and diverging object beams for each of the left and right eyes on the volume holographic recording material. For this, self-developing photopolymer films (Bayfol® HX) were used, since those simplify the manufacturing process of VHOEs substantially. Here, the directional lights are similar to the collimated reference beams that were used to record the VHOEs and create two diffracted beams similar to the object beams used for recording the VHOEs. Then, those diffracted beams read the left and right images alternately shown on the LCD panel and form two converging viewing zones in front of the user’s eyes. By this he can perceive the 3-D image. Theoretical predictions and experimental results are presented and the performance of the developed prototype is shown.

Video-based human activity recognition (HAR) means the analysis of motions and behaviors of human from the low level sensors. Over the last decade, automatic HAR is an exigent research area and is considered a significant concern in the field of computer vision and pattern recognition. In this paper, we have presented a robust and an accurate activity recognition system called WS-HAR that consists of wavelet transform coupled with stepwise linear discriminant analysis (SWLDA) followed by hidden Markov model (HMM). Symlet wavelet has been employed in order to extract the features from the activity frames. The most prominent features were selected by proposing a robust technique called stepwise linear discriminant analysis (SWLDA) that focuses on selecting the localized features from the activity frames and discriminating their class based on regression values (i.e., partial F-test values). Finally, we applied a well-known sequential classifier called hidden Markov model (HMM) to give the appropriate labels to the activities. In order to validate the performance of the WS-HAR, we utilized two publicly available standard datasets under two different experimental settings, n–fold cross validation scheme based on subjects; and a set of experiments was performed in order to show the effectiveness of each approach. The weighted average recognition rate for the WS-HAR was 97% across the two different datasets that is a significant improvement in classication accuracy compared to the existing well-known statistical and state-of-the-art methods.

A single SLM (spatial light modulator) full-color holographic 3-D display based on sampling and selective frequency-filtering methods is proposed. Spatially-sampled R(red), G(green) and B(blue)-holograms can provide periodic 3 × 3 arrays of their frequency spectrums. Thus, by allocating three groups of three spectrums to each color hologram, and selectively filtering out those spectrums with their own spectrum filtering masks (SFMs), frequency-filtered R, G and B-holograms can be obtained. These holograms are synthesized into a single color-multiplexed hologram, and optically reconstructed into a color distortion-free full-color 3-D object on the 4-f lens system, where color-dispersion due to the pixelated structure of the SLM can be removed with the optical versions of SFMs. Fourier-optical analysis and experiments with 3-D color objects in motion confirm the feasibility of the proposed system in the practical application.

A novel approach for fast generation of video holograms of three-dimensional (3-D) moving objects using a motion compensation-based novel-look-up-table (MC-N-LUT) method is proposed. Motion compensation has been widely employed in compression of conventional 2-D video data because of its ability to exploit high temporal correlation between successive video frames. Here, this concept of motion-compensation is firstly applied to the N-LUT based on its inherent property of shift-invariance. That is, motion vectors of 3-D moving objects are extracted between the two consecutive video frames, and with them motions of the 3-D objects at each frame are compensated. Then, through this process, 3-D object data to be calculated for its video holograms are massively reduced, which results in a dramatic increase of the computational speed of the proposed method. Experimental results with three kinds of 3-D video scenarios reveal that the average number of calculated object points and the average calculation time for one object point of the proposed method, have found to be reduced down to 86.95%, 86.53% and 34.99%, 32.30%, respectively compared to those of the conventional N-LUT and temporal redundancy-based N-LUT (TR-N-LUT) methods.