Yoong Choon Chang

A low-complexity unequal error protection of H.264/AVC video using adaptive hierarchical QAM

In this paper, a low-complexity unequal error protection (UEP) of H.264/AVC coded video using adaptive hierarchical quadrature amplitude modulation (HQAM), which takes into consideration the non-uniformly distributed importance of intracoded frame (I-frame) and predictive coded frame (P-frame) is proposed. Simulation results show that in terms of average peak signal-to-noise ratio (average PSNR), our proposed (EEP) scheme outperforms the equal error protection (EEP) by up to 5 dB

A low complexity hierarchical QAM symbol bits allocation algorithm for unequal error protection of wireless video transmission

A low complexity hierarchical quadrature amplitude modulation (QAM) symbol bits allocation algorithm for unequal error protection of video transmission over wireless channels is proposed in this paper. An unequal error protection (UEP) scheme using hierarchical QAM, which takes into consideration the non-uniformly distributed importance of intracoded frame (I-frame) and predictive coded frame (P-frame) in a group of pictures (GOP), is first proposed. In order to optimally allocate the hierarchical QAMs high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H.264/AVC video, a generic solution for optimal allocation of hierarchical QAMs high priority (HP), medium priority (MP) and low priority (LP) symbol bits to the H.264/AVC video is then proposed. Finally, a low complexity symbol bits allocation algorithm, namely ranking search algorithm, which reduces the computational complexity of the proposed optimal symbol bits allocation algorithm, is proposed. Simulation results show that our proposed UEP scheme outperforms the classical equal error protection (EEP) scheme and also the previous UEP scheme.

A simple vision-based fall detection technique for indoor video surveillance

Falls are one of the major health hazards among the aging population aged 65 and above, which could potentially result in a significant hindrance to their independent living. With the advances in medical science in the last few decades, the aging population increases every year, and thus, fall detection system at home is increasingly important. This paper presents a new vision-based fall detection technique that is based on human shape variation where only three points are used to represent a person instead of the conventional ellipse or bounding box. Falls are detected by analyzing the shape change of the human silhouette through the features extracted from the three points. Experiment results show that in comparison with the conventional ellipse and bounding box techniques, the proposed three point–based technique increases the fall detection rate without increasing the computational complexity.

A fast forward error correction allocation algorithm for unequal error protection of video transmission over wireless channels

A new fast forward error correction (FEC) allocation algorithm for unequal error protection (UEP) of video transmission over wireless channels is proposed in this paper. First, an UEP scheme, which takes into consideration the non-uniformly distributed importance of frames in a group of pictures (GOP) and macroblocks in a video frame, is proposed. An enhanced video error propagation model, namely expected number of macroblocks error propagation (ENMEP) is also proposed in this paper to measure the amount of error propagation caused by transmission errors. Finally, by making use of our proposed ENMEP error propagation model, a fast FEC allocation algorithm for our proposed UEP scheme is also proposed. Simulation results demonstrate that our scheme outperforms the previous UEP scheme and the classical equal error protection (EEP) scheme.

Cognitive VANET with enhanced priority scheme

Vehicular communications are important to ensure emergency messages are transmitted on time to prevent accidents. Therefore, in recent years, various standardization bodies and automobile companies have developed vehicular ad hoc network (VANET) to ensure public road safety. The current IEEE802.11p schemes utilize only traffic type to categorize priority levels. However, accidents are prone to occur when vehicles are in close distance. Therefore, based on the latest standard draft of IEEE1609.4 and IEEE802.11p, the proposed scheme, namely Enhanced Priority VANET Scheme (EPVS) is proposed where distance range between vehicles is derived and transmission priority level is categorized based on reliable distance range and data type. Performance of the proposed EPVS is evaluated in Vehicles in Network Simulation (Veins) with road traffic simulator, Simulation of Urban mobility (SUMO) using a realistic urban map. Simulations results show that the proposed EPVS results in lower average delay, in comparison with the default IEEE802.11p scheme.

Joint optimization and threshold structure dynamic programming with enhanced priority scheme for adaptive VANET MAC

Nodes in vehicular ad-hoc network (VANET) are highly mobile, traversing in unpredictable and varying environment. Therefore, contention window size and transmission power should adapt according to the high mobility transmission environment. In this paper, we propose an adaptive VANET medium access control (MAC) layer with joint optimization for VANET (MACVS) which aims at minimizing average delay and maximizing packet success rate. An adaptive joint optimization with proposed threshold structure dynamic programming, with closed loop feedback control system, is designed to optimize contention window size and transmission power. Adaptive optimization is done based on road traffic conditions and transmission reliable distance range (depicted by interference and noise), by monitoring the continuous change and threshold of received signal strength to interference and noise ratio. Mathematical expressions have been developed for the MACVS optimization framework, and the produced analytical results show good agreement with the simulation results. Simulations with different arrival rates and urban map of city center show that the proposed MACVS with low complexity joint optimization effectively reduces end-to-end delay while achieving high packet success rate under various network traffic condition.

Improving VANET Performance with Heuristic and Adaptive Fuzzy Logic Scheme

Abstract Rapid topology change in vehicular ad hoc network (VANET) is common due to the inherent high mobility nodes and unpredictable environments in VANET. In order to ensure efficient packet transmission, nodes in VANET should react adaptively to topology change in VANET. In this paper, we present a new heuristic and adaptive fuzzy logic scheme (HaFL), which adapts the contention window size and transmission power according to network and traffic conditions. The current existing schemes in VANET utilize only a single parameter to optimize the contention window and transmission power without consideration on the effects of interference as one of the main factors in VANET transmission degradation. In VANET, packet loss can occur at different stages of transmission due to interference or due to elapsed time. In the proposed HaFL, fuzzy logic is used to adaptively optimize the contention window size based on three parameters namely collision rate, SINR and queue overflow which represent packet drop at different stages of transmission. Transmission power which is usually a static parameter is also optimized with consideration on the effects of VANET interference in the proposed HaFL. The performance of the proposed HaFL is evaluated in Vehicles in Network Simulation with road traffic simulator, Simulation of Urban mobility. Simulation results show that the proposed HaFL demonstrates adaptability with improved throughput, low end-to-end delay and higher packet success rate in comparison with the default IEEE802.11p and existing schemes.

Automatic identification of drinking activities at home using depth data from RGB-D camera

With the increasing elderly population all around the world, the healthcare services to elderly has become more important. Dementia is one of the common cognitive problems among the elderly population where a basic daily dining activity could be difficult for them to perform. Drinking activities is one of the most important daily needs to keep a person away from dehydrating. Most of the existing works on dining activities recognitions are mainly based on wearable sensors and sensor rich eating utensil. Although the accuracy for sensor based techniques is high, some of the elderly might be reluctant to wear, and some might even forgot to wear altogether. In this paper, we propose a novel system that is purely based on depth data from an RGB-D camera for drinking activities recognition. Dynamic time warping algorithm is used to recognize and detect the drinking activities.

A novel low complexity Local Hybrid Pseudo-SSIM-SATD distortion metric towards perceptual rate control

The front-end block-based video encoder applies an Image Quality Assessment (IQA) as part of the distortion metric. Typically, the distortion metric applies uniform weighting for the absolute differences within a Sub-Macroblock (Sub-MB) at any given time. As video is predominately designed for Humans, the distortion metric should reflect the Human Visual System (HVS). Thus, a perceptual distortion metric (PDM), will lower the convex hull of the Rate-Distortion (R-D) curve towards the origin, by removing perceptual redundancy and retaining perceptual clues. Structured Similarity (SSIM), a perceptual IQA, has been adapted via logarithmic functions to measure distortion, however, it is restricted to the Group of Picture level and hence unable to adapt to the local Sub-MB changes. This paper proposes a Local Hybrid Pseudo-SSIM-SATD (LHPSS) Distortion Metric, operating at the Sub-MB level and satisfying the Triangle Equality Rule (≤). A detailed discussion of LHPSSs Psuedo-SSIM model will illustrate how SSIM can be perceptually scaled within the distortion metric space of SATD using non-logarithmic functions. Results of HD video encoded across different QPs will be presented showing the competitive bit usage under IbBbBbBbP prediction structure for similar image quality. Finally, the mode decision choices superimposed on the Intra frame will illustrate that LHPSS lowers the R-D curve as homogeneous regions are represented with larger block size.

Software-based serverless endpoint video combiner architecture for high-definition multiparty video conferencing

This paper proposes an endpoint video combiner architecture in a multipoint control unit (MCU) system for high definition multiparty video conferencing. The proposed architecture addresses the current reliability, computational and quality drawbacks of a conventional centralized based video combiner architecture. This is achieved by redesigning the MCU video to move away the video combiner from the bridge and into the client endpoints. Moreover, the proposed architecture represents a serverless system and is able to scale a large number of clients at high resolutions in a multipoint video conferencing session. In order to realize this design, this paper also proposes a custom robust sustainable session management protocol which allows a dynamic multi-port management between the MCU video and client endpoints. In addition, the proposed custom session management protocol includes recommendation for a session protection structure. Experimental results suggest that the proposed architecture exhibits significant computational frame rate performance gains of up to 762.95% in comparison with the conventional centralized video combiner architecture based on a series of four and eight high definition combined video assessments. Moreover, reliability analysis suggests that the proposed architecture is also able to consistently sustain a high frame rate performance within a long duration high definition multipoint video conferencing session.