47269670
Motion estimation for content adaptive video compression
A multistage motion estimation scheme is proposed. The scheme extracts video characteristics by first performing an online video analysis separately for foreground and background regions. Motion parameters are extracted and passed to the next stage. The next stage includes a mathematical model for the block distortion surface (BDS) that enables the algorithm to accordingly adjust its search technique. The search is performed on a precise search area adaptive to the statistical property of the motion vector prediction error. Due to its self-tuning property, not only does the proposed scheme adapt to scenes by yielding better visual quality but it also yields a lower computational complexity, compared with the other predictive motion estimation algorithms on standard benchmark sequences
8440598
A rate control algorithm for wireless video transmission using perceptual tuning
In video transmission over two-way wireless channel automatic repeat request (ARQ) retransmission has been used to protect packets from losing, which also causes the channel throughput varying and brings more challenges to rate control of the video compression. This paper proposes a new rate control algorithm based on regions of interest (ROI), PID buffer controlling and perceptual tuning techniques, etc. It intelligently allocates bit budget among different regions and adapts to time-varying wireless channel so as to achieve better perceptual quality in ROI and depress the frame skipping. Simulation results illustrate that our algorithm effectively enhances the perceptual quality for ROI, significantly reduces the number of frame skipping, and thereby improves the smoothness of the video.
11930112
Fast motion estimation using hierarchical motion intensity structure
The embedded motion compensation model of the new H.264/AVC video coding standard dramatically increases the computational complexity of motion estimation. We propose a fast motion estimation algorithm using a hierarchical motion intensity structure to lower the computational complexity of the motion estimation in H.264/AVC. The proposed algorithm is mainly based on a multi-level motion intensity structure. It determines the motion intensity at three levels and, accordingly, uses different motion estimation techniques to find a more accurate, and faster, motion vector (MV). Experimental results show that the proposed algorithm provides promising performance in terms of the computational speedup and video reconstruction quality.
16353382
Determining the size of spatial clusters in focused tests: Comparing two methods by means of simulation in a GIS
Abstract. Based on a four-point evaluation system consisting of accuracy, consistency, power, and chance to commit type I errors, this study compares Tango's minimum p (MinP) and Stone's maximum relative risk (MaxRR) methods for detecting focused cluster size through simulations in GIS. It reveals that the MinP method is more effective than the MaxRR method. The MinP method exhibits higher levels of accuracy and consistency; and its power and chance to commit type I errors are similar to the MinP method. The MaxRR method has a tendency to underestimate the cluster size, while the MinP method tends to overestimate the cluster size, particularly when the clusters are relatively big and have high relative risk levels. In addition, the MinP method seems to be most effective in revealing the size of clusters when clusters are neither too strong nor too weak. The lowest detection rates for clustering occur when the clustering signal is relatively weak, which is easily understandable. In practice, it might be useful to use both the methods to estimate a range of possible cluster sizes, where the MaxRR method indicates the lower estimate, while the MinP method gives the higher estimate of the cluster size.
2615609
EigenNail for Finger Force Direction Recognition
This paper presents a technique termed eigennails to classify fingertip force during contact based on the coloration patterns in the fingernail and surrounding skin. Fingertip force is classified into six directions: no force, normal force only, two directions (left/right) of lateral shear force, and two directions (forward/backward) of longitudinal shear forces. Based on the face recognition technique eigenfaces, a small number of eigennails are sufficient to express the color pattern features for shear force direction classification. Results show that 98% of 960 fingernail images of 8 different subjects are correctly classified. The lowest imaging resolution without sacrificing classification accuracy is found to be 10-by-10.
205906582
Polygonal approximation using genetic algorithms
A polygon approximation method based on genetic algorithms is proposed in this paper. In the method, a chromosome is used to represent a polygon and is represented by a binary string. Each bit, called a gene, represents a point on the object curve. The objective function is defined as the integral square error between the given curve and the approximated polygon. Three genetic operators namely selection, crossover and mutation, have been constructed for this specific problem. The proposed method when compared with three existing methods can obtain superior approximation results with less error norm with respect to the original curves.
18826555
Transparent silica glasses containing single walled carbon nanotubes
Organic/inorganic matrix nanocomposites have been created using an acid catalyzed, tetraethyl orthosilicate-based sol-gel technique with single-walled carbon nanotubes (SWNTs). By utilizing nanotubes functionalized with the dendron methyl 3,5-di(methyltrigycoloxy)benzylic alcohol (IPEG), ultrasonic blending in the sol phase prior to gelation yields excellent dispersion characteristics of the nanotube phase. The glasses were densified by heating to 600 °C yielding 80% of theoretical density with little change in the optical appearance or behavior. These materials exhibited intrinsic Rayleigh scattering, suggesting near ideal dispersion. Nonlinear optical transmission was observed for 1064 and 532 nm light suggesting that the matrix has a strong broad band coupling to the optical field. Such composites allow for a host of applications based on the novel confinement properties of carbon nanotubes in a robust inorganic host.
12119839
Performance analysis of maximum intensity projection algorithm for display of MRA images
The maximum intensity projection (MIP) is a popularly used algorithm for display of MRA images, but its performance has not been rigorously analyzed before. In this paper, four measures are proposed for the performance of the MIP algorithm and the quality of images projected from three-dimensional (3-D) data, which are vessel voxel projection probability, vessel detection probability, false vessel probability, and vessel-tissue contrast-to-noise ratio (CNR). As side products, vessel-missing probability, vessel receiver operating characteristics (ROC's), and mean number of false vessels are also studied. Based on the assumptions that the intensities of vessel, tissue, and noise along a projection path are independent Gaussian, these measures are derived and obtained all in closed forms. All the measures are functions of explicit parameters: vessel-to-tissue noise ratio (VTNR) and CNR of 3 D data prior to the MIP, vessel diameter, and projection length. It is shown that the MIP algorithm increases the CNR of large vessels whose CNR prior to the MIP is high and whose diameters are large. The increase in CNR increases with projection path length. On the other hand, all the proposed measures indicate that the small vessels that have low CNR prior to the MIP and small diameters suffer from the MIP. The performance gets worse as projection path length increases. All measures demonstrate a better performance when the vessel diameter is larger. Other properties and possible applications of the derived measures are also discussed.