Reuben A. Farrugia

A Robust Error Detection Mechanism for H.264/AVC Coded Video Sequences Based on Support Vector Machines

Current trends in wireless communications provide fast and location-independent access to multimedia services. Due to its high compression efficiency, H.264/AVC is expected to become the dominant underlying technology in the delivery of future wireless video applications. The error resilient mechanisms adopted by this standard alleviate the problem of spatio-temporal propagation of visual artifacts caused by transmission errors by dropping and concealing all macroblocks (MBs) contained within corrupted segments, including uncorrupted MBs. Concealing these uncorrupted MBs generally causes a reduction in quality of the reconstructed video sequence.

Exploiting depth information for fast multi-view video coding

Multi-view video coding exploits inter-view redundancies to compress the video streams and their associated depth information. These techniques utilize disparity estimation techniques to obtain disparity vectors (DVs) across different views. However, these methods contribute to the majority of the computational power needed for multi-view video encoding. This paper proposes a solution for fast disparity estimation based on multi-view geometry and depth information. A DV predictor is first calculated followed by an iterative or a fast search estimation process which finds the optimal DV in the search area dictated by the predictor. Simulation results demonstrate that this predictor is reliable enough to determine the area of the optimal DVs to allow a smaller search range. Furthermore, results show that the proposed approach achieves a speedup of 2.5 while still preserving the original rate-distortion performance.

Wireless propagation modelling inside a business jet

Wireless communication on-board aircraft has recently received increased attention as passengers are demanding for seamless office-like communication environments during their flight. Aircraft manufacturers are also interested in this technology to reduce cable complexity and provide new in-flight services. Various technologies are being considered for this purpose, such as IEEE802.11a/b/g. A radio propagation map is necessary to determine the received signal strengths inside the environment and can be obtained either through accurate modelling or through a measurement campaign. A simulation model is more attractive as it can be used to identify ideal antenna locations that maximize coverage at the design stage. Since the business jet market necessitates customized cabin configurations for each customer this will avoid costly measurement campaigns. This work presents a novel simulation model which has been used to characterize propagation characteristics inside a Dassault Aviation business jet. The developed package is based on geometric optics (GO) and adopts ray tracing techniques. Simulation results were compared with actual measurements performed on-board the aircraft with a good correlation between the two. This study takes into account only a static channel whereby all passengers are seated.

Robust decoder-based error control strategy for recovery of H.264/AVC video content

Real-time wireless conversational and broadcasting multimedia applications offer particular transmission challenges as reliable content delivery cannot be guaranteed. The undelivered and erroneous content causes significant degradation in quality of experience. The H.264/AVC standard includes several error resilient tools to mitigate this effect on video quality. However, the methods implemented by the standard are based on a packet-loss scenario, where corrupted slices are dropped and the lost information concealed. Partially damaged slices still contain valuable information that can be used to enhance the quality of the recovered video. This study presents a novel error recovery solution that relies on a joint source-channel decoder to recover only feasible slices. A major advantage of this decoder-based strategy is that it grants additional robustness while keeping the same transmission data rate. Simulation results show that the proposed approach manages to completely recover 30.79% of the corrupted slices. This provides frame-by-frame peak signal-to-noise ratio (PSNR) gains of up to 18.1 dB, a result which, to the knowledge of the authors, is superior to all other joint source-channel decoding methods found in literature. Furthermore, this error resilient strategy can be combined with other error resilient tools adopted by the standard to enhance their performance.

A Support Vector Machine Approach for Detection and Localization of Transmission Errors Within Standard H.263++ Decoders

Wireless multimedia services are increasingly becoming popular boosting the need for better quality-of-experience (QoE) with minimal costs. The standard codecs employed by these systems remove spatio-temporal redundancies to minimize the bandwidth required. However, this increases the exposure of the system to transmission errors, thus presenting a significant degradation in perceptual quality of the reconstructed video sequences. A number of mechanisms were investigated in the past to make these codecs more robust against transmission errors. Nevertheless, these techniques achieved little success, forcing the transmission to be held at lower bit-error rates (BERs) to guarantee acceptable quality. This paper presents a novel solution to this problem based on the error detection capabilities of the transport protocols to identify potentially corrupted group-of-blocks (GOBs). The algorithm uses a support vector machine (SVM) at its core to localize visually impaired macroblocks (MBs) that require concealment within these GOBs. Hence, this method drastically reduces the region to be concealed compared to state-of-the-art error resilient strategies which assume a packet loss scenario. Testing on a standard H.263++ codec confirms that a significant gain in quality is achieved with error detection rates of 97.8% and peak signal-to-noise ratio (PSNR) gains of up to 5.33 dB. Moreover, most of the undetected errors provide minimal visual artifacts and are thus of little influence to the perceived quality of the reconstructed sequences.

Driver fatigue monitoring system using Support Vector Machines

Driver fatigue is one of the leading causes of traffic accidents. This paper presents a real-time non-intrusive fatigue monitoring system which exploits the drivers facial expression to detect and alert fatigued drivers. The presented approach adopts the Viola-Jones classifier to detect the drivers facial features. The correlation coefficient template matching method is then applied to derive the state of each feature on a frame by frame basis. A Support Vector Machine (SVM) is finally integrated within the system to classify the facial appearance as either fatigued or otherwise. Using this simple and cheap implementation, the overall system achieved an accuracy of 95.2%, outperforming other developed systems employing expensive hardware to reach the same objective.

Exploiting depth information for fast motion and disparity estimation in Multi-view Video Coding

Multi-view Video Coding (MVC) employs both motion and disparity estimation within the encoding process. These provide a significant increase in coding efficiency at the expense of a substantial increase in computational requirements. This paper presents a fast motion and disparity estimation technique that utilizes the multi-view geometry together with the depth information and the corresponding encoded motion vectors from the reference view, to produce more reliable motion and disparity vector predictors for the current view. This allows for a smaller search area which reduces the computational cost of the multi-view encoding system. Experimental results confirm that the proposed techniques can provide a speed-up gain of up to 4.2 times, with a negligible loss in the rate-distortion performance for both the color and the depth MVC.

Enhancing the Error Detection Capabilities of the Standard Video Decoder using Pixel Domain Dissimilarity Metrics

The video compression standards commonly adopted in wireless multimedia services utilize variable length codes (VLC) in order to attain high compression ratios. While providing the high data rates required, this technique makes the system more susceptible to transmission errors. Thus the end-to-end quality of the video stream transmitted over an error-prone channel depends on the detection, and concealment of the corrupted macroblocks. The error detection capability of standard decoders is quite limited, for example, in the case of the H.263+ codec around 40.54% of the corrupted macroblocks are undetected, placing a bound on the perceived quality of the reconstructed video sequence. This paper presents a novel solution using eight pixel domain dissimilarity metrics computed in the CIE LUV color space which can be used at decode time to improve the error detection rate of the standard decoder. The spatial dissimilarity metric has been found to perform the best with an average increase in error detection rate of 60.38% when compared to the standard decoder (about 20% more than other published results) with 0% of false detection and a gain in peak signal-to-noise ratio (PSNR) of 3.94 dB.

A Hybrid Error Control and Artifact Detection Mechanism for Robust Decoding of H.264/AVC Video Sequences

This letter presents a hybrid error control and artifact detection (HECAD) mechanism which can be used to enhance the error resilient capabilities of the standard H.264/advanced video coding (AVC) codec. The proposed solution first exploits the residual source redundancy to recover the most likelihood H.264/AVC bitstream. If error recovery is unsuccessful, the residual corrupted slices are then passed through a pixel-level artifact detection mechanism to detect the visually impaired macroblocks to be concealed. The proposed HECAD algorithm achieves overall peak signal-to-noise ratio gains between 0.4 dB and 4.5 dB relative to the standard with no additional bandwidth requirement. The cost of this solution translates in a marginal increase in the complexity of the decoder. In addition, this method can be applied in conjunction with other error resilient strategies and scales well with different encoding configurations.

Exploiting depth information for efficient Multi-View Video Coding

The Multi-view Video Coding (MVC) technique provides significantly better coding efficiency compared to simulcast transmission of different camera view-points. This is done by exploiting both motion and disparity compensation techniques to compress the different view-point videos. This paper proposes a more efficient MVC technique that transmits the optimally selected compensation replacements with respect to more accurate compensation vector predictors obtained using the multi-view geometry and the depth information. In this technique, the SKIP mode is also modified to adapt its compensation direction from both the temporal and the view-point reference frames. Experimental results show that the proposed MVC technique gives an average gain in video quality of about 0.5dB, for the interview predicted view-points.