A novel depth edge prioritization based coding technique to boost-UP HEVC performance
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2016
- Type: Text , Conference paper
- Relation: 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
- Full Text: false
- Reviewed:
- 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.
A novel motion classification based intermode selection strategy for HEVC performance improvement
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Journal article
- Relation: Neurocomputing Vol. 173, no. Part 3 (2015), p. 1211-1220
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
- Reviewed:
- Description: High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC.
- Description: High Efficiency Video Coding (HEVC) standard adopts several new approaches to achieve higher coding efficiency (approximately 50% bit-rate reduction) compared to its predecessor H.264/AVC with same perceptual image quality. Huge computational time has also increased due to the algorithmic complexity of HEVC compared to H.264/AVC. However, it is really a demanding task to reduce the encoding time while preserving the similar quality of the video sequences. In this paper, we propose a novel efficient intermode selection technique and incorporate into HEVC framework to predict motion estimation and motion compensation modes between current and reference blocks and perform faster inter mode selection based on three dissimilar motion types in divergent video sequences. Instead of exploring and traversing all the modes exhaustively, we merely select a subset of candidate modes and the final mode from the selected subset is determined based on their lowest Lagrangian cost function. The experimental results reveal that average encoding time can be downscaled by 40% with similar rate-distortion performance compared to the exhaustive mode selection strategy in HEVC. © 2015 Elsevier B.V.
A novel no-reference subjective quality metric for free viewpoint video using human eye movement
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2018
- Type: Text , Conference proceedings
- 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)
A novel quality metric using spatiotemporal correlational data of human eye maneuver
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2017
- Type: Text , Conference proceedings
- 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
An analysis of human engagement behaviour using descriptors from human feedback, eye tracking, and saliency modelling
- Authors: Podder, Pallab , Paul, Manoranjan , Debnath, Tanmoy , Murshed, Manzur
- Date: 2015
- Type: Text , Conference proceedings
- Relation: 2015 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2015, Adelaide, 23-25th Nov 2015 in Digital Image Computing: Techniques and Applications (DICTA), 2015 International Conference
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text: false
- Reviewed:
- Description: In this paper an analysis of human engagement behaviour with video is presented based on real life experiments. An engagement model could be employed in classroom education, enhancing programming skills, reading etc. Two groups of people, independent of one another, watched eighteen video clips separately at different times. The first group's participants' eye gaze locations, right and left pupil sizes, and eye blinking patterns are recorded by a state of the art Tobii eye tracker. The second group of people who are video experts opined about the most significant attention points of the videos. A well-known bottom-up visual saliency model, Graph-Based Visual Saliency (GBVS), is also utilized to create salient points for the videos. Taking into consideration all the above mentioned descriptors the introduced behaviour analysis demonstrates the level of participants' concentration with the videos.
Efficient coding strategy for HEVC performance improvement by exploiting motion features
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Conference paper
- Relation: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing, Brisbane, QLD, 19th-24th April, 2015 p. 1414-1418
- Full Text: false
- Reviewed:
- Description: The striking feature of High Efficiency Video Coding (HEVC) Standard is emphasized by 50% bit-rate reduction compared to its predecessor H.264/AVC while keeping the same perceptual image quality. The time complexity - a congenital issue of HEVC has also increased to intensify the compression ratio. However, it is really a demanding task for the researchers to reduce the encoding time while preserving expected quality of the video sequences. Our contribution is to trim down the computational time by efficient selection of appropriate block-partitioning modes in HEVC using motion features based on phase-correlation. In this paper, we use phase-correlation between current and reference blocks to extract three motion features and combine them to determine binary motion pattern of the current block. The motion pattern is then matched against a codebook of predefined pattern templates to determine a subset of the inter-modes. Only the selected modes are exhaustively motion estimated and compensated for a coding unit. The experimental outcomes demonstrate that the average computational time can be down scaled by 30% of the HEVC while providing improved rate-distortion performance.
Efficient HEVC scheme using motion type categorization
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2014
- Type: Text , Conference proceedings
- Relation: 10th International Conference on emerging Networking EXperiments and Technologies (CoNEXT); Sydney, Australia; 2nd-5th December 2014; published in Proceedings of the 2014 Workshop on Design, Quality and Deployment of Adaptive Video Streaming p. 41-42
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text:
- Reviewed:
- Description: High Efficiency Video Coding (HEVC) standard introduces a number of innovative tools which can reduce approximately 50% bit-rate compared to its predecessor H.264/AVC at the same perceptual video quality whereas the computational time has increased multiple times. To reduce the encoding time while preserving the expected video quality has become a real challenge today for video transmission and streaming especially using low-powered devices. Motion estimation (ME) and motion compensation (MC) using variable-size blocks (i.e., intermodes) require 60-80% of total computational time. In this paper we propose a new efficient intermode selection technique based on phase correlation and incorporate into HEVC framework to predict ME and MC modes and perform faster intermode selection based on three dissimilar motion types in different videos. Instead of exploring all the modes exhaustively we select a subset of modes using motion type and the final mode is selected based on the Lagrangian cost function. The experimental results show that compared to HEVC the average computational time can be downscaled by 34% while providing the similar rate-distortion (RD) performance.
Efficient video coding using visual sensitive information for HEVC coding standard
- 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.
Fast coding strategy for HEVC by motion features and saliency applied on difference between successive image blocks
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Conference proceedings
- Relation: ConferencePacific-Rim Symposium on Image and Video Technology, Auckland, 23-27th Nov, 2016, In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).9431 p. 175-186
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text:
- Reviewed:
- Description: Introducing a number of innovative and powerful coding tools, the High Efficiency Video Coding (HEVC) standard promises double compression efficiency, compared to its predecessor H.264, with similar perceptual quality. The increased computational time complexity is an important issue for the video coding research community as well. An attempt to reduce this complexity of HEVC is adopted in this paper, by efficient selection of appropriate block-partitioning modes based on motion features and the saliency applied to the difference between successive image blocks. As this difference gives us the explicit visible motion and salient information, we develop a cost function by combining the motion features and image difference salient feature. The combined features are then converted into area of interest (AOI) based binary pattern for the current block. This pattern is then compared with a previously defined codebook of binary pattern templates for a subset of mode selection. Motion estimation (ME) and motion compensation (MC) are performed only on the selected subset of modes, without exhaustive exploration of all modes available in HEVC. The experimental results reveal a reduction of 42% encoding time complexity of HEVC encoder with similar subjective and objective image quality.
Fast inter-mode decision strategy for HEVC on depth videos
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 18th International Conference on Computer and Information Technology (ICCIT) p. 288-293
- Full Text: false
- Reviewed:
- Description: Multiview video employs the utilization of both texture and depth video information from different angles to create a 3D video for more realistic view of a scene. Unlike texture, depth video is a gray scale map that represents the distance between the camera and 3D points in a scene. Existing multiview video coding (MVC) techniques including 3D-High Efficiency Video Coding (HEVC) standard encode both texture and depth videos jointly by exploiting texture video information for the corresponding depth video coding (DVC) to reduce computational time as the texture and depth videos have motion similarity in representing the same scene. This strategy has two limitations: (i) more bits and computational time might be required due to the large residuals for the misalignment between depth and texture edges and (ii) switching between different views may require more times due to the increased dependency between texture and depth. In this paper, we propose an independent DVC technique using HEVC (a video coding standard for single view) so that we can improve the rate distortion (RD) performance and reduce computational time by improving switching speed. For this, we use motion features to reduce a number of motion estimation (ME) and motion compensation (MC) modes in HEVC. As we use motion feature which is the underlying criteria for selecting different modes in the standard and then we select a subset of modes which can provide almost the same RD performance. Experimental outcomes reveal a reduction of 48% encoding time of HEVC encoder with similar RD performance and better interactivity.
Fast intermode selection for HEVC video coding using phase correlation
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur , Chakraborty, Subrata
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014; Wollongong, Australia; 25th-27th November 2014 p. 1-8
- Relation: http://purl.org/au-research/grants/arc/DP130103670
- Full Text:
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- Description: The recent High Efficiency Video Coding (HEVC) Standard demonstrates higher rate-distortion (RD) performance compared to its predecessor H.264/AVC using different new tools especially larger and asymmetric inter-mode variable size motion estimation and compensation. This requires more than 4 times computational time compared to H.264/AVC. As a result it has always been a big concern for the researchers to reduce the amount of time while maintaining the standard quality of the video. The reduction of computational time by smart selection of the appropriate modes in HEVC is our motivation. To accomplish this task in this paper, we use phase correlation to approximate the motion information between current and reference blocks by comparing with a number of different binary pattern templates and then select a subset of motion estimation modes without exhaustively exploring all possible modes. The experimental results exhibit that the proposed HEVC-PC (HEVC with Phase Correlation) scheme outperforms the standard HEVC scheme in terms of computational time while preserving-the same quality of the video sequences. More specifically, around 40% encoding time is reduced compared to the exhaustive mode selection in HEVC. © 2014 IEEE.
- Description: 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014
Fast mode decision in the HEVC Video coding standard by exploiting region with dominated motion and saliency features
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2012
- Type: Text , Journal article
- Relation: PLoS ONE Vol. Vol.11, no. 3 (2012), p. p.e0150673
- Full Text:
- Reviewed:
- Description: The emerging High Efficiency Video Coding (HEVC) standard introduces a number of innovative and powerful coding tools to acquire better compression efficiency compared to its predecessor H.264. The encoding time complexities have also increased multiple times that is not suitable for realtime video coding applications. To address this limitation, this paper employs a novel coding strategy to reduce the time complexity in HEVC encoder by efficient selection of appropriate block-partitioning modes based on human visual features (HVF). The HVF in the proposed technique comprise with human visual attention modelling-based saliency feature and phase correlation-based motion features. The features are innovatively combined through a fusion process by developing a content-based adaptive weighted cost function to determine the region with dominated motion/saliency (RDMS)- based binary pattern for the current block. The generated binary pattern is then compared with a codebook of predefined binary pattern templates aligned to the HEVC recommended block-paritioning to estimate a subset of inter-prediction modes. Without exhaustive exploration of all modes available in the HEVC standard, only the selected subset of modes are motion estimated and motion compensated for a particular coding unit. The experimental evaluation reveals that the proposed technique notably down-scales the average computational time of the latest HEVC reference encoder by 34% while providing similar rate-distortion (RD) performance for a wide range of video sequences.
Foreground motion and spatial saliency-based efficient HEVC Video Coding
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2015
- Type: Text , Conference paper
- Relation: 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ)
- Full Text: false
- Reviewed:
- Description: High Efficiency Video Coding (HEVC) could not provide real time facilities to the limited processing and battery powered electronic devices as its encoding time complexity increases multiple times compared to its predecessor. Numerous researchers contribute to address this limitation by reducing a number of motion estimation (ME) modes where they analyze homogeneity, residual and statistical correlation among different modes. Although their approaches save some encoding time, however, could not reach the similar rate-distortion (RD) performance with HEVC encoder as they merely depend on existing Lagrangian cost function (LCF) within HEVC framework. To overcome this limitation, in this paper, we capture visual attentive Foreground motion and salient region (FMSR) which are sensitive to human visual system for quality assessment. The FMSR features captured by visual attentive and dynamic background modeling are adaptively synthesized to determine a subset of candidate modes. This preprocessing phase is independent from LCF. Since the proposed technique can avoid exhaustive exploration of all modes with simple criteria, it can reduce 27% encoding time on average. With efficient selection of FMSR-based appropriate block partitioning modes, it can also improve up to 1.0dB peak signal-to-noise ratio (PSNR).
Improved depth coding for HEVC focusing on depth edge approximation
- Authors: Podder, Pallab , Paul, Manoranjan , Rahaman, Motiur , Murshed, Manzur
- Date: 2017
- Type: Text , Journal article , acceptedVersion
- 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.
Joint texture and depth coding using cuboid data compression
- Authors: Paul, Manoranjan , Chakraborty, Subrata , Murshed, Manzur , Podder, Pallab
- Date: 2015
- Type: Text , Conference proceedings
- Relation: 2015 18th International Conference on Computer and Information Technology (ICCIT); Dhaka, Bangladesh; 21st-23rd December 2015 p. 138-143
- Full Text:
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- Description: The latest multiview video coding (MVC) standards such as 3D-HEVC and H.264/MVC normally encodes texture and depth videos separately. Significant amount of rate-distortion performance and computational performance are sacrificed due to separate encoding due to the lack of exploitation of joint information. Obviously, separate encoding also creates synchronization issue for 3D scene formation in the decoder. Moreover, the hierarchical frame referencing architecture in the MVC creates random access frame delay. In this paper we develop an encoder and decoder framework where we can encode texture and depth video jointly by forming and encoding 3D cuboid using high dimensional entropy coding. The results from our experiments show that our proposed framework outperforms the 3D-HEVC in rate-distortion performance and reduces the computational time significantly by reducing random access frame delay.
QMET : A new quality assessment metric for no-reference video coding by using human eye traversal
- Authors: Podder, Pallab , Paul, Manoranjan , Murshed, Manzur
- Date: 2016
- Type: Text , Conference proceedings
- 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