A perceptual based rate control scheme for MPEG-2

In this paper, a new perceptual based rate control algorithm for MPEG-2 is presented. The algorithm first determines the target bit count for each frame using simple statistical models. Precise bit allocation is used to adjust the macroblock quantization scale factors to meet the given bit count, with the uniform visual fidelity as the primary objective. Since the buffer is very stable, it is less sensitive to transmission delay, Experimental results showed that it gave better visual quality and less buffer variations as compared to the TM5 rate control scheme.published_or_final_versio

A new fast motion estimation algorithm using hexagonal subsampling pattern and multiple candidates search

In this paper we present a fast algorithm to reduce the computational complexity of block motion estimation. The reduction is obtained from the use of a new hexagonal subsampling pattern and the domain decimation method introduced by Cheng and Chan (see Proc. IEEE ICASSP, vol.4, p.2313, 1996). The multiple candidates search method is also introduced to improve the robustness of the algorithm. Computer simulation shows that the performance is very close to that of the full search.published_or_final_versio

Post-processing of transform coded images using selective filtering and fuzzy-based enhancement

Transform coding often leads to artifacts called blocking when the image or video is compressed to low bit-rate. In this paper, a new post-processing scheme using selective low-pass filtering and fuzzy-based enhancement is proposed. The merit of the scheme is that it can remove most of the blocking artifacts found in image or video coding while preserving most of the fine details. Simulation results demonstrated that the proposed algorithm can significantly improve the visual quality of the decoded image.published_or_final_versio

A two-stage bivariate logistic-Tobit model for the safety analysis of signalized intersections

Crash frequency and crash severity models have explored the factors that influence intersection safety. However, most of these models address the frequency and severity independently, and miss the correlations between crash frequency models at different crash severity levels. We develop a two-stage bivariate logistic-Tobit model of the crash severity and crash risk at different severity levels. The first stage uses a binary logistic model to determine the overall crash severity level. The second stage develops a bivariate Tobit model to simultaneously evaluate the risk of a crash resulting in a slight injury and the risk of a crash resulting in a kill or serious injury (KSI). The model uses 420 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during 2002 and 2003. The results obtained from the first-stage binary logistic model indicate that the overall crash severity level is significantly influenced by the annual average daily traffic and number of pedestrian crossings. The results obtained from the second-stage bivariate Tobit model indicate that the factor that significantly influences the numbers of both slight injury and KSI crashes is the proportion of commercial vehicles. The existence of four or more approaches, the reciprocal of the average turning radius and the presence of a turning pocket increase the likelihood of slight injury crashes. The average lane width and cycle time affect the likelihood of KSI crashes. A comparison with existing approaches suggests that the bivariate logistic-Tobit model provides a good statistical fit and offers an effective alternative method for evaluating the safety performance at signalized intersections.postprin

Multiresolution motion compensation coding for video compression

Motion estimation using block matching algorithm (BMA) is frequently used to reduced the temporal redundancy found in video coding. The performance of the mean squared error (MSE) is usually better than the mean absolute difference (MAD). However, the computational complexity is higher due to the squaring operations. In this paper, we propose a multiple candidates approach to shorten the gap between the two methods with slight increase in computational complexity. Application of the proposed algorithm to subband motion-estimation is studied and simulation results demonstrate that great improvement in performance can be obtained with similar computational complexity as the MAD measure.published_or_final_versio

Quasi-induced exposure method for pedestrian safety at signalized intersections

postprin

Generalized camera calibration model for trapezoidal patterns on the road

published_or_final_versio

Continuum modeling approach to the spatial analysis of air quality and housing location choice

Today, air pollution is a great issue, and the transport sector is an important emission source. In this study, we present an integrated land use, transport, and environment model in which transport-related pollutants are assumed to influence people's housing location choices, and a continuum modeling approach is applied. The pollutants generated by the transport sector are dispersed by the wind and they affect air quality. The air quality changes people's housing choices, which in turn changes their travel behavior. We assume that the road users are continuously distributed over the city, that the road network is relatively dense, and that this network can be approximated as a continuum. The total demand is categorized into several classes, and the modeled region contains several subdistricts. People who live in different subdistricts or who belong to different classes of commuters are assumed to have different perceptions of travel time, air quality, and the housing provision–demand relationship. The finite element method and the Newton–Raphson algorithm are adopted to solve this problem, and a numerical valuation is given to illustrate the effectiveness and efficiency of the proposed model.postprin

Real-Time Estimation of Lane-to-Lane Turning Flows at Isolated Signalized Junctions

published_or_final_versio

Potential field cellular automata model for pedestrian flow

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced. © 2012 American Physical Society.published_or_final_versio