Dumidu S. Talagala

Energy-Efficient Location and Activity-Aware On-Demand Mobile Distributed Sensing Platform for Sensing as a Service in IoT Clouds

The Internet of Things (IoT) envisions billions of sensors deployed around us and connected to the Internet, where the mobile crowd sensing technologies are widely used to collect data in different contexts of the IoT paradigm. Due to the popularity of Big Data technologies, processing and storing large volumes of data have become easier than ever. However, large-scale data management tasks still require significant amounts of resources that can be expensive regardless of whether they are purchased or rented (e.g., pay-as-you-go infrastructure). Further, not everyone is interested in such large-scale data collection and analysis. More importantly, not everyone has the financial and computational resources to deal with such large volumes of data. Therefore, a timely need exists for a cloud-integrated mobile crowd sensing platform that is capable of capturing sensors data, on-demand, based on conditions enforced by the data consumers. In this paper, we propose a context-aware, specifically, location and activity-aware mobile sensing platform called context-aware mobile sensor data engine (C-MOSDEN) for the IoT domain. We evaluated the proposed platform using three real-world scenarios that highlight the importance of selective sensing. The computational effectiveness and efficiency of the proposed platform are investigated and are used to highlight the advantages of context-aware selective sensing.

Efficient multi-channel adaptive room compensation for spatial soundfield reproduction using a modal decomposition

Mitigating the effects of reverberation is a significant challenge for real-world spatial soundfield reproduction, but the necessity of a large number of reproduction channels increases the complexity and presents several challenges to existing listening room compensation techniques. In this paper, we present an adaptive room compensation method to overcome the effects of reverberation within a region, using a model description of the reverberant soundfield. We propose the reverberant channel estimation and compensation be carried out in a single step using completely decoupled adaptive filters; thus, reducing the complexity of the overall process. We compare the soundfield reproduction performance with existing adaptive and nonadaptive room compensation methods through several simulation examples. The performance of the proposed method is comparable to existing techniques, and achieves a normalized wideband region reproduction error of 1% at a signal-to-noise ratio of 50 dB, within a 1 m radius region of interest using 60 loudspeakers and 55 microphones at frequencies below 1 kHz. Robust behavior of the room compensator is demonstrated down to direct-to-reverberant-path power ratios of -5 dB. Overall, the results suggest that the proposed method can diagonalize the room compensation system, leading to a more robust and parallel implementation for spatial soundfield reproduction.

Binaural sound source localization using the frequency diversity of the head-related transfer function

The spectral localization cues contained in the head-related transfer function are known to play a contributory role in the sound source localization abilities of humans. However, existing localization techniques are unable to fully exploit this diversity to accurately localize a sound source. The availability of just two measured signals complicates matters further, and results in front to back confusions and poor performance distinguishing between the source locations in a vertical plane. This study evaluates the performance of a source location estimator that retains the frequency domain diversity of the head-related transfer function. First, a method for extracting the directional information in the subbands of a broadband signal is described, and a composite estimator based on signal subspace decomposition is introduced. The localization performance is experimentally evaluated for single and multiple source scenarios in the horizontal and vertical planes. The proposed estimators ability to successfully localize a sound source and resolve the ambiguities in the vertical plane is demonstrated, and the impact of the source location, knowledge of the source and the effect of reverberation is discussed.

Broadband DOA Estimation Using Sensor Arrays on Complex-Shaped Rigid Bodies

Sensor arrays mounted on complex-shaped rigid bodies are a common feature in many practical broadband direction of arrival (DOA) estimation applications. The scattering and reflections caused by these rigid bodies introduce complexity and diversity in the frequency domain of the channel transfer function, which presents several challenges to existing broadband DOA estimators. This paper presents a novel high resolution broadband DOA estimation technique based on signal subspace decomposition. We describe how broadband signals can be decomposed into narrow subband components, and combined such that the frequency domain diversity is retained. The DOA estimation performance is compared with existing techniques using a uniform circular array and a sensor array on a hypothetical rigid body. An improvement in closely spaced source resolution of up to 6 dB is observed for the sensor array on the hypothetical rigid body, in comparison to the uniform circular array. The results suggest that frequency domain diversity, introduced by complex-shaped rigid bodies, can provide higher resolution and clearer separation of closely spaced broadband sound sources.

Adaptive residual mapping for an efficient extension layer coding in two-layer HDR video coding

In the absence of a commercial High Dynamic Range (HDR) distribution pipeline, two-layer backward-compatible HDR video coding is a viable solution for the imminent transition from Low Dynamic Range (LDR) to HDR content transmission. However, the performance of a two-layer coding solution is governed by the extension layer coding performance. In this paper, we propose an improved two-layer backward-compatible HDR video coding solution based on an adaptive residual mapping for the extension layer, keeping in view the performance of High Efficiency Video Coding (HEVC) being used to code this information. The proposed solution outperforms the reference method achieving averaged PU-PSNR improvements of up to 5.05 dB. The proposed method also shows potential of achieving the same HDR quality as the single layer coding solution with a minimum bitrate overhead and acceptable LDR quality in the base layer.

Active acoustic echo cancellation in spatial soundfield reproduction

The equalization of reverberation effects is essential for spatial soundfield reproduction, but estimation of the reverberant channel presents several challenges to existing equalization techniques. This paper presents a method of active acoustic echo cancellation (AEC) for soundfield reproduction applications, using a modal description of the reverberant soundfield. We describe how individual modes of the measured soundfield can be equalized adaptively, thus reducing the complexity of the channel estimation process. AEC and reproduction performance is compared with existing adaptive and non-adaptive equalization techniques through simulation examples. Equalization performance is comparable to existing methods, achieving a normalized region reproduction error of 1% and echo return loss enhancement of 15 - 30 dB at 50 dB SNR. The results suggest that the proposed model can be used to obtain a parallel implementation of a room equalizer for active AEC.

Error resilience aware motion estimation and mode selection for HEVC video transmission

Error concealment techniques such as motion copying require significant changes to HEVC (High Efficiency Video Coding) motion estimation process when incorporated in error resilience frameworks. This paper demonstrates a novel motion estimation mechanism incorporating the concealment impact from future coding frames to achieve an average 0.73 dB gain over the state-of-the-art.

RATE DISTORTION ANALYSIS OF HIGH DYNAMIC RANGE VIDEO CODING TECHNIQUES

High Dynamic Range (HDR) is a key technology envisioned to provide the end-users a sense of “being there”. With the advent of HDR displays in the near future, it is not clear if the existing content distribution environment will be capable of supporting HDR. Although it is generally argued that single-layer HDR coding solutions are superior to two-layer backward-compatible techniques, these coding strategies have not been fully investigated in terms of their rate distortion trade-off. In this paper, three main HDR coding techniques are implemented to analyze their performance and to evaluate the potential of HDR content distribution, while minimizing the impact on existing infrastructure, i.e., in terms of bitrate and HDR quality trade-off. The results reveal that backward-compatible solutions can outperform the single-layer approach achieving PSNR_DE improvements of up to 3.05dB on average. The HDR-VDP-2 quality indexes show similar improvements further confirming the superior performance of the backward-compatible solutions.

CTU level decoder energy consumption modelling for decoder energy-aware HEVC encoding

Accurate modelling of the decoding energy of a CTU is essential to determine the appropriate level of quantization required for decoder energy-aware video encoding. The proposed method predicts the number of nonzero DCT coefficients, and their energy requirements with an average accuracy of 4.8% and 11.19%, respectively.

Improved Two-Layer backward-compatible HDR video coding: A performance comparison with Single-Layer HLG

Two-Layer HDR video coding based on an adaptive residual mapping with extension layer coding performance optimized for HEVC is proposed in this paper. The proposed solution, while maintaining backward-compatibility, outperforms the state-of-the art Single-Layer HLG broadcast pipeline achieving higher HDR quality in terms of both HDR-VDP-2.2 and HDR-VQM along with acceptable LDR quality in the base layer.