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A novel no-reference subjective quality metric for free viewpoint video using human eye movement

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2018
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 8th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2017; Wuhan, China; 20th-24th November 2017; published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10749 LNCS, p. 237-251
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  • Description: The free viewpoint video (FVV) allows users to interactively control the viewpoint and generate new views of a dynamic scene from any 3D position for better 3D visual experience with depth perception. Multiview video coding exploits both texture and depth video information from various angles to encode a number of views to facilitate FVV. The usual practice for the single view or multiview quality assessment is characterized by evolving the objective quality assessment metrics due to their simplicity and real time applications such as the peak signal-to-noise ratio (PSNR) or the structural similarity index (SSIM). However, the PSNR or SSIM requires reference image for quality evaluation and could not be successfully employed in FVV as the new view in FVV does not have any reference view to compare with. Conversely, the widely used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain knowledge, and many other factors that may actively influence on actual assessment. To address this limitation, in this work, we devise a no-reference subjective quality assessment metric by simply exploiting the pattern of human eye browsing on FVV. Over different quality contents of FVV, the participants eye-tracker recorded spatio-temporal gaze-data indicate more concentrated eye-traversing approach for relatively better quality. Thus, we calculate the Length, Angle, Pupil-size, and Gaze-duration features from the recorded gaze trajectory. The content and resolution invariant operation is carried out prior to synthesizing them using an adaptive weighted function to develop a new quality metric using eye traversal (QMET). Tested results reveal that the proposed QMET performs better than the SSIM and MOS in terms of assessing different aspects of coded video quality for a wide range of FVV contents.
  • Description: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Efficient video coding using visual sensitive information for HEVC coding standard

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2018
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 6, no. (2018), p. 75695-75708
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  • Description: The latest high efficiency video coding (HEVC) standard introduces a large number of inter-mode block partitioning modes. The HEVC reference test model (HM) uses partially exhaustive tree-structured mode selection, which still explores a large number of prediction unit (PU) modes for a coding unit (CU). This impacts on encoding time rise which deprives a number of electronic devices having limited processing resources to use various features of HEVC. By analyzing the homogeneity, residual, and different statistical correlation among modes, many researchers speed-up the encoding process through the number of PU mode reduction. However, these approaches could not demonstrate the similar rate-distortion (RD) performance with the HM due to their dependency on existing Lagrangian cost function (LCF) within the HEVC framework. In this paper, to avoid the complete dependency on LCF in the initial phase, we exploit visual sensitive foreground motion and spatial salient metric (FMSSM) in a block. To capture its motion and saliency features, we use the dynamic background and visual saliency modeling, respectively. According to the FMSSM values, a subset of PU modes is then explored for encoding the CU. This preprocessing phase is independent from the existing LCF. As the proposed coding technique further reduces the number of PU modes using two simple criteria (i.e., motion and saliency), it outperforms the HM in terms of encoding time reduction. As it also encodes the uncovered and static background areas using the dynamic background frame as a substituted reference frame, it does not sacrifice quality. Tested results reveal that the proposed method achieves 32% average encoding time reduction of the HM without any quality loss for a wide range of videos.

Exploiting user provided information in dynamic consolidation of virtual machines to minimize energy consumption of cloud data centers

- Khan, Anit, Paplinski, Andrew, Khan, Abdul, Murshed, Manzur, Buyya, Rajkumar

  • Authors: Khan, Anit , Paplinski, Andrew , Khan, Abdul , Murshed, Manzur , Buyya, Rajkumar
  • Date: 2018
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 3rd International Conference on Fog and Mobile Edge Computing, FMEC 2018; Barcelona, Spain; 23rd-26th April 2018; p. 105-114
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  • Description: Dynamic consolidation of Virtual Machines (VMs) can effectively enhance the resource utilization and energy-efficiency of the Cloud Data Centers (CDC). Existing research on Cloud resource reservation and scheduling signify that Cloud Service Users (CSUs) can play a crucial role in improving the resource utilization by providing valuable information to Cloud service providers. However, utilization of CSUs' provided information in minimization of energy consumption of CDC is a novel research direction. The challenges herein are twofold. First, finding the right benign information to be received from a CSU which can complement the energy-efficiency of CDC. Second, smart application of such information to significantly reduce the energy consumption of CDC. To address those research challenges, we have proposed a novel heuristic Dynamic VM Consolidation algorithm, RTDVMC, which minimizes the energy consumption of CDC through exploiting CSU provided information. Our research exemplifies the fact that if VMs are dynamically consolidated based on the time when a VM can be removed from CDC-a useful information to be received from respective CSU, then more physical machines can be turned into sleep state, yielding lower energy consumption. We have simulated the performance of RTDVMC with real Cloud workload traces originated from more than 800 PlanetLab VMs. The empirical figures affirm the superiority of RTDVMC over existing prominent Static and Adaptive Threshold based DVMC algorithms.

Texture based vein biometrics for human identification : A comparative study

- Bashar, Khayrul, Murshed, Manzur

  • Authors: Bashar, Khayrul , Murshed, Manzur
  • Date: 2018
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 42nd IEEE Computer Software and Applications Conference, COMPSAC 2018; Tokyo, Japan; 23rd-27th July 2018 Vol. 2, p. 571-576
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  • Description: Hand vein biometric is an important modality for human authentication and liveness detection in many applications. Reliable feature extraction is vital to any biometric system. Over the past years, two major categories of vein features, namely vein structures and vein image textures, were proposed for hand dorsal vein based biometric identification. Of them, texture features seem important as it can combine skin micro-textures along with vein properties. In this study, we have performed a comparative study to identify potential texture features and feature-classifier combination that produce efficient vein biometric systems. Seven texture features (HOG, GABOR, GLCM, SSF, DWT, WPT, and LBP) and three multiclass classifiers (LDA, ESVM, and KNN) were explored towards the supervised identification of human from vein images. An experiment with 400 infrared (IR) hand images from 40 adults indicates the superior performance of the histogram of oriented gradients (HOG) and simple local statistical feature (SSF) with LDA and ESVM classifiers in terms of average accuracy (> 90%), average Fscore (> 58%) and average specificity (>93%). The decision-level fusion of the LDA and ESVM classifier with single texture features showed improved performances (by 2.2 to 13.2% of average Fscore) over individual classifier for human identification with IR hand vein images.
  • Description: Proceedings - International Computer Software and Applications Conference

A novel quality metric using spatiotemporal correlational data of human eye maneuver

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2017
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 2017 International Conference on Digital Image Computing : Techniques and Applications, DICTA 2017; Sydney, Australia; 29th November-1st December 2017 Vol. 2017-December, p. 1-8
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  • Description: The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate more concentrated eye- traversing approach for relatively better quality. We calculate the Length, Angle, Pupil-size, and Gaze-duration features from the recorded gaze trajectory. The content and resolution invariant operation is carried out prior to synthesizing them using an adaptive weighted function to develop a new quality metric using eye traversal (QMET). Tested results reveal that the quality evaluation carried out by QMET demonstrates a strong correlation with the most widely used peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and the MOS.
  • Description: DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications

Adaptive weighted non-parametric background model for efficient video coding

- Chakraborty, Subrata, Paul, Manoranjan, Murshed, Manzur, Ali, Mortuza

  • Authors: Chakraborty, Subrata , Paul, Manoranjan , Murshed, Manzur , Ali, Mortuza
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Neurocomputing Vol. 226, no. (2017), p. 35-45
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  • Description: Dynamic background frame based video coding using mixture of Gaussian (MoG) based background modelling has achieved better rate distortion performance compared to the H.264 standard. However, they suffer from high computation time, low coding efficiency for dynamic videos, and prior knowledge requirement of video content. In this paper, we introduce the application of the non-parametric (NP) background modelling approach for video coding domain. We present a novel background modelling technique, called weighted non-parametric (WNP) which balances the historical trend and the recent value of the pixel intensities adaptively based on the content and characteristics of any particular video. WNP is successfully embedded into the latest HEVC video coding standard for better rate-distortion performance. Moreover, a novel scene adaptive non-parametric (SANP) technique is also developed to handle video sequences with high dynamic background. Being non-parametric, the proposed techniques naturally exhibit superior performance in dynamic background modelling without a priori knowledge of video data distribution.

An algorithm for network and data-aware placement of multi-tier applications in cloud data centers

- Ferdaus, Md Hasanul, Murshed, Manzur, Calheiros, Rodrigo, Buyya, Rajkumar

  • Authors: Ferdaus, Md Hasanul , Murshed, Manzur , Calheiros, Rodrigo , Buyya, Rajkumar
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Journal of Network and Computer Applications Vol. 98, no. (2017), p. 65-83
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  • Description: Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance bottleneck. This paper addresses network-aware placement of virtual components (computing and data) of multi-tier applications in data centers and formally defines the placement as an optimization problem. The simultaneous placement of Virtual Machines and data blocks aims at reducing the network overhead of the data center network infrastructure. A greedy heuristic is proposed for the on-demand application components placement that localizes network traffic in the data center interconnect. Such optimization helps reducing communication overhead in upper layer network switches that will eventually reduce the overall traffic volume across the data center. This, in turn, will help reducing packet transmission delay, increasing network performance, and minimizing the energy consumption of network components. Experimental results demonstrate performance superiority of the proposed algorithm over other approaches where it outperforms the state-of-the-art network-aware application placement algorithm across all performance metrics by reducing the average network cost up to 67% and network usage at core switches up to 84%, as well as increasing the average number of application deployments up to 18%. © 2017 Elsevier Ltd

Cuboid segmentation for effective image retrieval

- Murshed, Manzur, Teng, Shyh, Lu, Guojun

  • Authors: Murshed, Manzur , Teng, Shyh , Lu, Guojun
  • Date: 2017
  • Type: Text , Conference proceedings
  • Relation: 2017 International Conference on Digital Image Computing : Techniques and Applications (DICTA); Sydney, Australia; 29th November-1st December 2017 p. 884-891
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  • Description: Region-based image retrieval has been proven to be effective in finding relevant images. In this paper, we propose a cuboid im-age segmentation method which results in rectangle image partitions. Rectangle partitions are more suitable for image compression, retrieval and other image operations. We apply partitions in image retrieval in this paper. Our experimental results have shown that (1) the proposed partitioning method is effective in segmenting images into meaningful rectangles; (2) using colour partitions for image retrieval is more effective than using whole images; and (3) the partitioned approach has additional advantage of letting users to select certain objects/colours as queries to find more relevant images/objects. These three advantages could be important in crime scene investigation image indexing and retrieval. Moreover, the proposed technique is amenable to compressed-domain applications.

Dynamic virtual machine consolidation algorithms for energy-efficient cloud resource management : A review

- Khan, Md Anit, Paplinski, Andrew, Khan, Abdul, Murshed, Manzur, Buyya, Rajkumar

  • Authors: Khan, Md Anit , Paplinski, Andrew , Khan, Abdul , Murshed, Manzur , Buyya, Rajkumar
  • Date: 2017
  • Type: Text , Book chapter
  • Relation: Sustainable Cloud and Energy Services : Principles and Practice Chapter 6 p. 135-165
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  • Description: As envisioned by Leonard Kleinrock [1], Cloud computing has transformed the dream of “computing as a utility” into reality, so much so it has turned out as the latest computing paradigm [2]. Cloud computing is called as Service-on-demand, as Cloud Service Providers (CSPs) assure users about potentially unlimited amount of resources that can be chartered on demand. It is also known as elastic computing, since Cloud Service Users (CSUs) can dynamically scale, expand, or shrink their rented resources anytime and expect to pay for the exact tenure of resource usage under Service Level Agreements (SLA). Through such flexibilities and financial benefits, CSPs have been attracting millions of clients who are simultaneously sharing the underlying computing and storage resources that are collectively known as Cloud data centers.

Improved depth coding for HEVC focusing on depth edge approximation

- Podder, Pallab, Paul, Manoranjan, Rahaman, Motiur, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Rahaman, Motiur , Murshed, Manzur
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Signal Processing: Image Communication Vol. 55, no. (2017), p. 80-92
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  • Description: The latest High Efficiency Video Coding (HEVC) standard has greatly improved the coding efficiency compared to its predecessor H.264. An important share of which is the adoption of hierarchical block partitioning structures and an extended number of modes. The structure of existing inter-modes is appropriate mainly to handle the rectangular and square aligned motion patterns. However, they could not be suitable for the block partitioning of depth objects having partial foreground motion with irregular edges and background. In such cases, the HEVC reference test model (HM) normally explores finer level block partitioning that requires more bits and encoding time to compensate large residuals. Since motion detection is the underlying criteria for mode selection, in this work, we use the energy concentration ratio feature of phase correlation to capture different types of motion in depth object. For better motion modeling focusing at depth edges, the proposed technique also uses an extra pattern mode comprising a group of templates with various rectangular and non-rectangular object shapes and edges. As the pattern mode could save bits by encoding only the foreground areas and beat all other inter-modes in a block once selected, the proposed technique could improve the rate-distortion performance. It could also reduce encoding time by skipping further branching using the pattern mode and selecting a subset of modes using innovative pre-processing criteria. Experimentally it could save 29% average encoding time and improve 0.10 dB Bjontegaard Delta peak signal-to-noise ratio compared to the HM.

A Centroid Algorithm for Stabilization of Turbulence-Degraded Underwater Videos

- Halder, Kalyan Kumar, Paul, Manoranjan, Tahtali, Murat, Anavatti, Sreenatha G., Murshed, Manzur

  • Authors: Halder, Kalyan Kumar , Paul, Manoranjan , Tahtali, Murat , Anavatti, Sreenatha G. , Murshed, Manzur
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 2016 International Conference on Digital Image Computing: Techniques and Applications DICTA 2016 p. 1-6
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  • Description: This paper addresses the problem of stabilizing underwater videos with non-uniform geometric deformations or warping due to a wavy water surface. It presents an improved method to correct these geometric deformations of the frames, providing a high-quality stabilized video output. For this purpose, a non-rigid image registration technique is employed to accurately align the warped frames with respect to a prototype frame and to estimate the deformation parameters, which in turn, are applied in an image dewarping technique. The prototype frame is chosen from the video sequence based on a sharpness assessment. The effectiveness of the proposed method is validated by applying it on both synthetic and real- world sequences using various quality metrics. A performance comparison with an existing method confirms the higher efficacy of the proposed method.

A novel depth edge prioritization based coding technique to boost-UP HEVC performance

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
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  • Description: In addition to the texture, multiview video employs the utilization of depth coding for the reconstruction of 3D video and Free viewpoint video. Standing on some texture-depth correlations, a number of methods in literature reuses texture motion vector for the corresponding depth coding to reduce encoding time by avoiding costly motion estimation process. However, texture similarity metric is not always equivalent to the corresponding depth similarity metric especially at edge levels. Since their approaches could not explicitly detect and encode acute edge motions of depth objects, eventually, could not reach the similar or improved rate-distortion (RD) performance against the High Efficiency Video Coding (HEVC) reference test model (HM). With a view to more accurate motion detection and modeling, the proposed technique exploits an extra Pattern Mode comprising a group of pattern templates (GPTs) with different rectangular and non-rectangular object shapes and edges compared to the existing HEVC block partitioning modes. Moreover, the proposed Pattern Mode only encodes the motion areas and skips the background areas. The experimental results show that the proposed technique could save 30% encoding time and improve average 0.1dB Bjontegard Delta peak signal-to-noise ratio (BD-PSNR) compared to the HM.

Anonymization techniques for preserving data quality in participatory sensing

- Sabrina, Tishna, Murshed, Manzur, Iqbal, Anindya

  • Authors: Sabrina, Tishna , Murshed, Manzur , Iqbal, Anindya
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 2016 IEEE 41st Conference on Local Computer Networks (LCN) p. 607-610
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  • Description: Participatory sensing is a revolutionary new paradigm where citizens voluntarily sense their surroundings using readily available sensing devices such as mobile phones and share this information for mutual benefit of community members. To encourage ample participation of users, ensuring their privacy is inevitable. Existing techniques that attempt to protect location privacy with spatial cloaking suffer from irrecoverable data quality degradation. To the best of our knowledge, very few works provided a solution preserving high data quality/utility at the destination server, however, suffered from unacceptable computational overhead. This paper presents an improved deterministic alternative and also a faster variant by exploiting several optimization issues. Theoretical formulations and extensive simulation results are presented to establish the applicability of our proposed techniques.

Lossless depth map coding using binary tree based decomposition and context-based arithmetic coding

- Shahriyar, Shampa, Murshed, Manzur, Ali, Mortuza, Paul, Manoranjan

  • Authors: Shahriyar, Shampa , Murshed, Manzur , Ali, Mortuza , Paul, Manoranjan
  • Date: 2016
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 2016 IEEE International Conference on Multimedia and Expo, ICME 2016; Seattle, United States; 11th-15th July 2016; published in Proceedings of the 2016 IEEE International Conference on Mulitmedia and Expo Vol. 2016-August, p. 1-6
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  • Description: Depth maps are becoming increasingly important in the context of emerging video coding and processing applications. Depth images represent the scene surface and are characterized by areas of smoothly varying grey levels separated by sharp edges at the position of object boundaries. To enable high quality view rendering at the receiver side, preservation of these characteristics is important. Lossless coding enables avoiding rendering artifacts in synthesized views due to depth compression artifacts. In this paper, we propose a binary tree based lossless depth coding scheme that arranges the residual frame into integer or binary residual bitmap. High spatial correlation in depth residual frame is exploited by creating large homogeneous blocks of adaptive size, which are then coded as a unit using context based arithmetic coding. On the standard 3D video sequences, the proposed lossless depth coding has achieved compression ratio in the range of 20 to 80. © 2016 IEEE.
  • Description: Proceedings - IEEE International Conference on Multimedia and Expo

Lossless hyperspectral image compression using binary tree based decomposition

- Shahriyar, Shampa, Paul, Manoranjan, Murshed, Manzur, Ali, Mortuza

  • Authors: Shahriyar, Shampa , Paul, Manoranjan , Murshed, Manzur , Ali, Mortuza
  • Date: 2016
  • Type: Text , Conference proceedings
  • Relation: 2016 International Conference on Digital Image Computing: Techniques and Applications (Dicta); Gold Coast, Australia; 30th November-2nd December 2016 p. 428-435
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  • Description: A Hyperspectral (HS) image provides observational powers beyond human vision capability but represents more than 100 times data compared to a traditional image. To transmit and store the huge volume of an HS image, we argue that a fundamental shift is required from the existing "original pixel intensity"based coding approaches using traditional image coders (e.g. JPEG) to the "residual" based approaches using a predictive coder exploiting band-wise correlation for better compression performance. Moreover, as HS images are used in detection or classification they need to be in original form; lossy schemes can trim off uninteresting data along with compression, which can be important to specific analysis purposes. A modified lossless HS coder is required to exploit spatial- spectral redundancy using predictive residual coding. Every spectral band of an HS image can be treated like they are the individual frame of a video to impose inter band prediction. In this paper, we propose a binary tree based lossless predictive HS coding scheme that arranges the residual frame into integer residual bitmap. High spatial correlation in HS residual frame is exploited by creating large homogeneous blocks of adaptive size, which are then coded as a unit using context based arithmetic coding. On the standard HS data set, the proposed lossless predictive coding has achieved compression ratio in the range of 1.92 to 7.94. In this paper, we compare the proposed method with mainstream lossless coders (JPEG-LS and lossless HEVC). For JPEG-LS, HEVCIntra and HEVCMain, proposed technique has reduced bit-rate by 35%, 40% and 6.79% respectively by exploiting spatial correlation in predicted HS residuals.

Lossless image coding using hierarchical decomposition and recursive partitioning

- Ali, Mortuza, Murshed, Manzur, Shahriyar, Shampa, Paul, Manoranjan

  • Authors: Ali, Mortuza , Murshed, Manzur , Shahriyar, Shampa , Paul, Manoranjan
  • Date: 2016
  • Type: Text , Journal article
  • Relation: APSIPA Transactions on Signal and Information Processing Vol. 5, no. (2016), p. 1-11
  • Relation: http://purl.org/au-research/grants/arc/DP130103670
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  • Description: State-Of-The-Art lossless image compression schemes, such as JPEG-LS and CALIC, have been proposed in the context-adaptive predictive coding framework. These schemes involve a prediction step followed by context-adaptive entropy coding of the residuals. However, the models for context determination proposed in the literature, have been designed using ad-hoc techniques. In this paper, we take an alternative approach where we fix a simpler context model and then rely on a systematic technique to efficiently exploit spatial correlation to achieve efficient compression. The essential idea is to decompose the image into binary bitmaps such that the spatial correlation that exists among non-binary symbols is captured as the correlation among few bit positions. The proposed scheme then encodes the bitmaps in a particular order based on the simple context model. However, instead of encoding a bitmap as a whole, we partition it into rectangular blocks, induced by a binary tree, and then independently encode the blocks. The motivation for partitioning is to explicitly identify the blocks within which the statistical correlation remains the same. On a set of standard test images, the proposed scheme, using the same predictor as JPEG-LS, achieved an overall bit-rate saving of 1.56% against JPEG-LS. © 2016 The Authors.

Poster : Privacy protection for real world participatory sensing system

- Abrar, Nafeez, Iqbal, Anindya, Zaman, Shaolin, Murshed, Manzur

  • Authors: Abrar, Nafeez , Iqbal, Anindya , Zaman, Shaolin , Murshed, Manzur
  • Date: 2016
  • Type: Text , Conference paper
  • Relation: 14th Annual International Conference on Mobile Systems, Applications, and Services Companion
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  • Description: Participatory Sensing System (PSS) is an emerging technology for collection of useful information as the use of smart-phones has been increasing lately among community people. It has a wide range of applications like environmental monitoring, product price sharing, health monitoring etc. But people have to share their location and other information which is a high privacy risk. Our main contribution of this work is to develop a technique for PSS which can provide privacy protection for the participants in manageable time in real world.

QMET : A new quality assessment metric for no-reference video coding by using human eye traversal

- Podder, Pallab, Paul, Manoranjan, Murshed, Manzur

  • Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
  • Date: 2016
  • Type: Text , Conference proceedings , Conference Paper
  • Relation: 2016 International Conference on Image and Vision Computing New Zealand, IVCNZ 2016; Palmerston North, New Zealand; 21st-22nd November 2016 p. 1-6
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  • Description: The subjective quality assessment (SQA) is an ever demanding approach due to its in-depth interactivity to the human cognition. The addition of no-reference based scheme could equip the SQA techniques to tackle further challenges. Existing widely used objective metrics-peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) or the subjective estimator-mean opinion score (MOS) requires original image for quality evaluation that limits their uses for the situation having no-reference. In this work, we present a no-reference based SQA technique that could be an impressive substitute to the reference-based approaches for quality evaluation. The High Efficiency Video Coding (HEVC) reference test model (HM15.0) is first exploited to generate five different qualities of the HEVC recommended eight class sequences. To assess different aspects of coded video quality, a group of ten participants are employed and their eye-tracker (ET) recorded data demonstrate closer correlation among gaze plots for relatively better quality video contents. Therefore, we innovatively calculate the amount of approximation of smooth eye traversal (ASET) by using distance, angle, and pupil-size feature from recorded gaze trajectory data and develop a new-quality metric based on eye traversal (QMET). Experimental results show that the quality evaluation carried out by QMET is highly correlated to the HM recommended coding quality. The performance of the QMET is also compared with the PSNR and SSIM metrics to justify the effectiveness of each other.
  • Description: International Conference Image and Vision Computing New Zealand

Search and tracking algorithms for swarms of robots: A survey

- Senanayake, Madhubhashi, Senthooran, Ilankaikaone, Barca, Jan Carlo, Chung, Hoam, Kamruzzaman, Joarder, Murshed, Manzur

  • Authors: Senanayake, Madhubhashi , Senthooran, Ilankaikaone , Barca, Jan Carlo , Chung, Hoam , Kamruzzaman, Joarder , Murshed, Manzur
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Robotics and Autonomous Systems Vol. 75, no. Part B (2016), p. 422-434
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  • Description: Target search and tracking is a classical but difficult problem in many research domains, including computer vision, wireless sensor networks and robotics. We review the seminal works that addressed this problem in the area of swarm robotics, which is the application of swarm intelligence principles to the control of multi-robot systems. Robustness, scalability and flexibility, as well as distributed sensing, make swarm robotic systems well suited for the problem of target search and tracking in real-world applications. We classify the works we review according to the variations and aspects of the search and tracking problems they addressed. As this is a particularly application-driven research area, the adopted taxonomy makes this review serve as a quick reference guide to our readers in identifying related works and approaches according to their problem at hand. By no means is this an exhaustive review, but an overview for researchers who are new to the swarm robotics field, to help them easily start off their research. © 2015 Elsevier B.V.

Workload-aware incremental repartitioning of shared-nothing distributed databases for scalable OLTP applications

- Kamal, Joarder, Murshed, Manzur, Buyya, Rajkumar

  • Authors: Kamal, Joarder , Murshed, Manzur , Buyya, Rajkumar
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Future Generation Computer Systems Vol. 56, no. March (2016), p. 421-436
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  • Description: On-line Transaction Processing (OLTP) applications often rely on shared-nothing distributed databases that can sustain rapid growth in data volume. Distributed transactions (DTs) that involve data tuples from multiple geo-distributed servers can adversely impact the performance of such databases, especially when the transactions are short-lived and these require immediate responses. The. k-way min-cut graph clustering based database repartitioning algorithms can be used to reduce the number of DTs with acceptable level of load balancing. Web applications, where DT profile changes over time due to dynamically varying workload patterns, frequent database repartitioning is needed to keep up with the change. This paper addresses this emerging challenge by introducing incremental repartitioning. In each repartitioning cycle, DT profile is learnt online and. k-way min-cut clustering algorithm is applied on a special sub-graph representing all DTs as well as those non-DTs that have at least one tuple in a DT. The latter ensures that the min-cut algorithm minimally reintroduces new DTs from the non-DTs while maximally transforming existing DTs into non-DTs in the new partitioning. Potential load imbalance risk is mitigated by applying the graph clustering algorithm on the finer logical partitions instead of the servers and relying on random one-to-one cluster-to-partition mapping that naturally balances out loads. Inter-server data-migration due to repartitioning is kept in check with two special mappings favouring the current partition of majority tuples in a cluster-the many-to-one version minimising data migrations alone and the one-to-one version reducing data migration without affecting load balancing. A distributed data lookup process, inspired by the roaming protocol in mobile networks, is introduced to efficiently handle data migration without affecting scalability. The effectiveness of the proposed framework is evaluated on realistic TPC-C workloads comprehensively using graph, hypergraph, and compressed hypergraph representations used in the literature. To compare the performance of any incremental repartitioning framework without any bias of the external min-cut algorithm due to graph size variations, a transaction generation model is developed that can maintain a target number of unique transactions in any arbitrary observation window, irrespective of new transaction arrival rate. The overall impact of DTs at any instance is estimated from the exponential moving average of the recurrence period of unique transactions to avoid transient fluctuations. The effectiveness and adaptability of the proposed incremental repartitioning framework for transactional workloads have been established with extensive simulations on both range partitioned and consistent hash partitioned databases. © 2015 Elsevier B.V.