Efficient pattern index coding using syndrome coding and side information
- Authors: Paul, Manoranjan , Murshed, Manzur
- Date: 2012
- Type: Text , Journal article
- Relation: International Journal of Engineering and Industries Vol. 3, no. 3 (2012), p. 1-12
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- Description: Pattern-based video coding focusing on moving regions has already established its superiority over the H.264 at very low bit rate. Up to a certain limit, the larger the number of pattern templates, thebetter the approximation to the moving regions. However, beyond that limit no coding gain is observed due to the need of an excessive number of pattern identification bits. Recently, distributed video codingschemes have used syndrome coding to predict the original information in the decoder using side information. In this paper a pattern identification scheme is proposed which predicts the pattern fromthe syndrome codes and side information in the decoder so that the actual pattern identification code is not needed. The experimental results confirm that the new scheme improves the rate-distortionperformance compared to the existing pattern-based video coding and compared with the H.264 standard. The proposed new scheme will also present opportunities for further syndrome codingapplication.
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
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- 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.
Impact on vertical handoff decision algorithm by the network call admission control policy in heterogeneous wireless networks
- Authors: Sharna, Shusmita , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications, Sydney, Sept. 9th-12th 2012, pp.893-898
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- Description: Vertical handoff plays an important role to provide seamless connectivity for a mobile user in an overlapped multinetwork environment. On the other hand in order to maintain network stability, efficient management of available radio resource becomes crucial as network operators want high network utilization and maximum profit generation. For vertical handoff management, existing research works considered these user centric vertical handoff decision algorithm and network centric call admission control as two isolated decision mechanisms in heterogeneous wireless environment. In this paper, however, we propose a correlation between vertical handoff decisions and call admission control policies. We have developed a novel vertical handoff decision model using the Markov decision process based vertical handoff decision algorithm by refining the optimality criterion to factor in the probabilistic consequence of the call dropping rates so that mobile-centric vertical handoff decision algorithm and network-centric call admission control can work through a feedback mechanism to maximize respective objectives in synergy.
Modelling sensing radius for efficient wireless sensor deployment
- Authors: Iqbal, Anindya , Murshed, Manzur
- Date: 2012
- Type: Text , Conference paper
- Relation: Proceedings of the International Symposium on Communications and Information Technologies, (ISCIT 2012), Gold Coast, 2nd-5th October. pp. 365-370
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- Description: In many application scenarios, wireless sensors are deployed deterministically throughout a wide area to detect and report specific events or monitor environmental parameters. To cover a large area with minimal number of sensors, it is important to determine sensing radius of the operating sensors. Since the emitted energy of a random event is neither predictable nor fixed, accurate sensing radius modelling is a challenging problem. To the best of our knowledge, no work has considered how the event intensity factor reduces probability of event detection while assuming a sensing radius despite its high significance in important areas such as coverage, detection, localization, etc. In this paper, we have proposed a novel stochastic model of the maximum sensing radius to guarantee a user-defined event detection probability from the pdf of average event intensity and the quality of sensors. Comprehensive theoretical and numerical analyses are presented to evaluate the event detection performance of this model against different relevant parameters and these are also verified by simulation. Provision for event location trajectory computation is analysed for high-intensity events.
Range-free passive localization using static and mobile sensors
- Authors: Iqbal, Anindya , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), San Francisco, CA, 25th-28th June, 2012 p. 1-6
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- Description: In passive localization, sensors try to locate an event without any knowledge of event's emitted power. So, this is a more challenging problem compared to active localization. Existing passive localization schemes use expensive and noise-vulnerable range-based techniques. In this paper, we propose, to the best of our knowledge for the first time, a cost-effective range-free passive localization scheme exploiting hybrid sensor network model where mobile sensors are deployed on demand once an event is sensed by a static sensor. Efficient use of mobile sensors leads to two concomitant optimization problems: (1) positioning the mobile sensors so that the expected possible event location area is minimized; and (2) minimizing their overall traversed distance. To solve the first problem, we have developed a novel arc-coding based range-free localization technique that can accurately define the area of possible event location from the feedback of arbitrarily placed sensors without relying on expensive hardware to estimate range of signals. We have achieved significantly high localization accuracy with a low number of mobile sensors even after considering significant environmental noise. To solve the second problem, three alternative deployment strategies for the mobile sensors were simulated to recommend the best.
Robust background subtraction based on perceptual mixture-of-Gaussians with dynamic adaptation speed
- Authors: Haque, Mahfuzul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 9th-13th July, Melbourne, 2012
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- Description: In this paper, we propose a new background subtraction technique based on perceptual mixture-of-Gaussians (PMOG). Unlike numerous variants of the classical MOG based approach [1], which can ensure reliable detection result only in known operating environments through proper parameter tuning, PMOG shows superior detection performance across dynamic unconstrained scenarios without any tuning. This is due to PMOG's intrinsic capability of exploiting several perceptual characteristics of human visual system for better understanding of the operating environment to avoid blind reliance on statistical observations. Furthermore, the proposed technique dynamically varies the model adaptation speed, i.e., learning rate, based on observed scene statistics for faster adaptation of changed background and better persistency of detected foreground entities. Comprehensive experimental evaluation on a number of standard datasets validates the robustness of the technique compared to the state-of-the-art.
Unsaturated throughput analysis of a novel interference-constrained multi-channel random access protocol for cognitive radio networks
- Authors: Hasan, Rashidul , Murshed, Manzur
- Date: 2012
- Type: Text , Conference proceedings
- Relation: Proceedings of the 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2012) Sydney 9-12th September, 2012 p. 178-194
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- Description: Opportunistic access of licensed spectrum using a cognitive radio network (CRN) is getting research attraction due to its ability to improve utilisation of this scarce resource without affecting the primary users (PUs). To improve wide acceptability of CRN, it must be equipped with efficient protocols to deal with multiple primary networks to provision QoS guarantee for demand-driven applications by the secondary users (SUs). In this paper, an accurate unsaturated throughput analysis is presented for our novel CSMA/CA-based multi-channel cognitive radio medium access control (MCR-MAC) protocol. Developed by modifying the 4-way handshaking-based IEEE 802.11 DCF, MCR-MAC dynamically assigns contending SUs to free channels using an innovative random arbitration scheme while keeping cognitive interference to the PUs in check by attenuating the packet size. Not only has the analytical model covered the full spectrum, from very light load to saturation, extensive simulation results have validated the accuracy of the analysis.
A Novel multichannel cognitive radio network with throughput analysis at saturation load
- Authors: Hasan, Rashidul , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: 10th IEEE International Symposium on Network Computing and Applications (NCA), 25-27th August, 2011 Cambridge, MA, p. 1-6
- Full Text: false
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- Description: Opportunistic access of licensed spectrum using a cognitive radio network (CRN) is getting research attraction due to its ability to improve utilisation of this scarce resource without affecting the primary users (PUs). To improve wide acceptability of CRN, it must be equipped with efficient protocols to deal with multiple primary networks to provision QoS guarantee for demand-driven applications by the secondary users (SUs). In this paper, a novel CSMA/CA-based multichannel cognitive radio medium access control (MCR-MAC) protocol is developed by modifying the 4-way handshaking based IEEE 802.11 DCF to dynamically assign contending SUs to free channels using an innovative random arbitration scheme. The paper also presents a detailed analytical model for cognitive interference to the PUs and SUs. The proposed protocol is designed to keep the interference level in check to remain transparent to the PUs. A throughput analysis at saturation load reveals that this fully ad-hoc MCR-MAC is capable of achieving throughput comparable to the ideal scenario (when SUs are equally divided to the channels) without using any centralised infrastructure or dedicated control channel. Extensive simulation results validate the accuracy of the theoretical analysis and establish MCR-MAC as a highly practical solution to construct a CRN in a region overlapped with multiple primary networks to offer data-rate sensitive applications by the SUs.
A subset coding based k-anonymization technique to trade-off location privacy and data integrity in participatory sensing systems
- Authors: Murshed, Manzur , Iqbal, Anindya , Sabrina, Tishna , Alam, K.
- Date: 2011
- Type: Text , Conference paper
- Full Text: false
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Action recognition using spatio-temporal distance classifier correlation filter
- Authors: Anwaar-Ul Haq , Gondal, Iqbal , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: 2011 International Conference on Digital Image Computing Techniques and Applications (DICTA), Noosa, QLD, 6th-8th Dec, 2011
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- Description: The problem of recognizing human actions is characterized by complex dynamics and strong variations in their executions. Despite this inconvenience, space-time correlations provide valuable clues for their discrimination. Therefore, space-time correlators like emph{Maximum Average Correlation Height} (MACH) filters have successfully been used for action recognition with encouraging results. However, their utility is challenged due to number of factors: (i) these filters are trained only for one class at a time and separate filters are required for each class increasing computational overhead, (ii) these filters simply take average of similar action instances and behave no better than average filters and (iii) misaligned action datasets create problems for these filters as they are not shift-invariant. In this paper, we address these issues by posing action recognition as a multi-class discrimination problem and propose a emph{single} 3D frequency domain filter, named Action ST-DCCF for multiple action classes that mitigates inherent discrepancies of correlation filters. It presents a different interpretation of correlation filters as a method of applying spatio-temporal transformation to the data rather than simply minimizing correlation energy across all possible shifts. Experiments on a variety of action datasets are performed to evaluate our approach. Experimental results are comparable to the existing action recognition approaches.
- Description: The problem of recognizing human actions is characterized by complex dynamics and strong variations in their executions. Despite this inconvenience, space-time correlations provide valuable clues for their discrimination. Therefore, space-time correlators like \emph{Maximum Average Correlation Height} (MACH) filters have successfully been used for action recognition with encouraging results. However, their utility is challenged due to number of factors: (i) these filters are trained only for one class at a time and separate filters are required for each class increasing computational overhead, (ii) these filters simply take average of similar action instances and behave no better than average filters and (iii) misaligned action datasets create problems for these filters as they are not shift-invariant. In this paper, we address these issues by posing action recognition as a multi-class discrimination problem and propose a \emph{single} 3D frequency domain filter, named Action ST-DCCF for multiple action classes that mitigates inherent discrepancies of correlation filters. It presents a different interpretation of correlation filters as a method of applying spatio-temporal transformation to the data rather than simply minimizing correlation energy across all possible shifts. Experiments on a variety of action datasets are performed to evaluate our approach. Experimental results are comparable to the existing action recognition approaches.
Ad hoc operations of enhanced IEEE 802.11 with multiuser dynamic OFDMA under saturation load
- Authors: Ferdous, Hasan , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
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- Description: In this paper, we discuss the challenges associated with integrating multiuser OFDMA in a single cell IEEE 802.11 based wireless ad hoc network and propose a new, dynamic and robust approach to improve it. Our new MAC, using OFDMA in the physical layer, can incorporate multiple concurrent transmissions or receptions in a dynamic manner and can adjust the collision probability based on the traffic load when nodes are endowed with a single half-duplex radio only. Simulation results show that for moderate number of users, our system improves throughput by up to 20%, decreases collision in control messages by up to 45% and reduces the average delay by up to 18%.
Adaptive weight factor estimation from user preferences for vertical handoff decision algorithms
- Authors: Sharna, Shusmita , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: IEEE Wireless Communications and Networking Conference (WCNC) (Mony de Swaan Adali 28 March 2011 to 31 March 2011) p. 1143-1148
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- Description: Estimating weight factors for QoS parameters plays an important role in the effectiveness of vertical handoff decision algorithms. This paper presents a novel weight estimation technique, which can adaptively control the spanning of the weights in response to user preference. Simulation results show the supremacy of the technique against the state-of-the-art in achieving wider spanning of the expected values of all QoS parameters under consideration.
An enhanced-MDP based vertical handoff algorithm for QoS support over heterogeneous wireless networks
- Authors: Sharna, Shusmita , Amin, Mohammad , Murshed, Manzur
- Date: 2011
- Type: Text , Conference proceedings
- Relation: Proceedings of 2011 IEEE International Symposium on Network Computing and Applications (NCA 2011),Cambridge, MA, 25-27th Aug, 2011
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- Description: Vertical handoff plays an important role in guaranteeing users to be always connected in an overlapped multi-network environment. During the vertical handoff procedure, handoff decision is the most important step that affects the normal working of communication. An incorrect handoff decision or selection of a non-optimal network may result in undesirable effects such as higher costs, poor quality of service (QoS) experience, and even dropped communication. Among the existing vertical handoff decision algorithms, the Markov Decision Process (MDP) based algorithm by Stevens-Navarro et al. is promising due to its ability to achieve the optimal expected reward. However, the reward function used by this algorithm is flawed as it favors reducing expected number of vertical handoffs at the expense of diminished expected values of other QoS parameters. This paper presents an extended MDP based algorithm (EMDP) with novel reward function formulation. Analysis shows that EMDP outperforms the MDP based algorithm in terms of improved expected values of all QoS parameters considered while keeping the vertical handoff number reasonably low.
Analytical modeling of enhanced IEEE 802.11 with multiuser dynamic OFDMA under saturation load
- Authors: Ferdous, Hasan , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: 17th Asia-Pacific Conference on Communications, APCC 2011 p. 524-529
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- Description: Multiuser dynamic OFDMA based IEEE 802.11 distributed coordination function (DCF) has received significant interest from the researchers in recent time. Though several proposals have been made, to the best of our knowledge, none of these have presented an analytical model for this kind of medium access control protocols for IEEE 802.11. This paper provides a simple, nevertheless, very accurate analytical model to estimate the performance characteristics of IEEE 802.11 DCF with OFDMA under the assumptions of ideal channel conditions and saturation load. Our model accounts for important system parameters like throughput, collision rate, transmission delay, average contention window size, average retry count and average time wasted in backoff. Analytical results are verified through extensive simulations.
Call admission control policy for multiclass traffic in heterogeneous wireless networks
- Authors: Sharna, Shusmita , Amin, Mohammad , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: International Symposium on Communications and Information Technologies (ISCIT) p. 433-438
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- Description: An increasing demand for wireless access to packetbased services has, in turn, driven the need for call admission control strategies to make network roaming more seamless. This paper investigates the optimal call admission control (CAC) policy for heterogeneous wireless networks based on Markov Decision Process (MDP) and Value Iteration Algorithm (VIA). We concentrate on the optimization problems of when different type of calls (i.e., new calls, vertical handoff calls, and horizontal handoff calls) can be admitted into the system where each call may have single or multiple channel requirements (multiclass). Experimental results confirm that the proposed technique can effectively control call admission of a highly dynamic heterogeneous system, which will be crucial for accommodating vertical handoff decision algorithms
Conflict resolution based global search operators for long protein structures prediction
- Authors: Islam, Md , Chetty, Madhu , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: 18th International Conference on Neural Information Processing, ICONIP 2011; Shanghai; China; 13th to 17th November 2011; published in Neural Information Processing, (Lecture Notes in Computer Science series) Vol. 7062 (1) p.636-645
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- Description: Most population based evolutionary algorithms (EAs) have struggled to accurately predict structure for long protein sequences. This is because conventional operators, i.e., crossover and mutation, cannot satisfy constraints (e.g., connected chain and self-avoiding-walk) of the complex combinatorial multi-modal problem, protein structure prediction (PSP). In this paper, we present novel crossover and mutation operators based on conflict resolution for handling long protein sequences in PSP using lattice models. To our knowledge, this is a pioneering work to address the PSP limitations for long sequences. Experiments carried out with long PDB sequences show the effectiveness of the proposed method. © 2011 Springer-Verlag.
Contextual action recognition in multi-sensor nighttime video sequences
- Authors: Anwaar-Ul, Haq , Gondal, Iqbal , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: Proceedings of the 2011 Digital Image Computing: Techniques and Applications (DICTA 2011), Noosa 6th-8th Dec, 2011 p. 256-261
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- Description: Contextual information is important for interpreting human actions especially when actions exhibit interactive relationship with their context. Contextual clues become even more crucial when videos are captured in unfavorable conditions like extreme low light nighttime scenarios. These conditions encourage the use of multi-senor imagery and context enhancement. In this paper, we explore the importance of contextual knowledge for recognizing human actions in multi-sensor nighttime videos. Information fusion is utilized for encapsulating visual information about actions and their context. Space-time action information is contained using 3D fourier transform of fused action silhouette volume. In parallel, SIFT context images are extracted and fused using principal component analysis based feature fusion for each action class. Contextual dissimilarity is penalized by minimizing context SIFT flow energy. The action dataset comprises multi-sensor night vision video data from infra-red and visible spectrum. Experimental results show that fused contextual action information boost action recognition performance as compared to the baseline action recognition approac
Demand-driven movement strategy for moving beacons in distributed sensor localization
- Authors: Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: International Conference on Computational Science (ICCS)
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- Description: n a wireless sensor network, range-free localization with a moving beacon can reduce susceptibility to communication noises while concomitantly eliminate need for large number of expensive anchor nodes that are vulnerable to malicious attacks. This paper presents a moving beacon aided range-free localization technique, which is capable of estimating the location of a sensor with high accuracy. A novel distributed localization scheme is designed to optimally determine beacon movement strategy according to user demand. Superiority of this scheme to the state-of-the-art has been established in terms of location estimation quality, measured by the theoretical expected maximum error and simulated mean error while optimizing the beacon location density or traversal path length.
Novel local improvement techniques in clustered memetic algorithm for protein structure prediction
- Authors: Islam, Md Kamrul , Chetty, Madhu , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: IEEE Congress on Evolutionary Computation (IEEE CEC) p. 1003-1011
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- Description: Evolutionary algorithms (EAs) often fail to find the global optimum due to genetic drift. As the protein structure prediction problem is multimodal having several global optima, EAs empowered with combined application of local and global search e.g., memetic algorithms, can be more effective. This paper introduces two novel local improvement techniques for the clustered memetic algorithm to incorporate both problem specific and search-space specific knowledge to find one of the optimum structures of a hydrophobic-polar protein sequence on lattice models. Experimental results show the superiority of the proposed techniques against existing EAs on benchmark sequences.
On dynamic scene geometry for view-invariant action matching
- Authors: Ul-Haq, Anwaar , Gondal, Iqbal , Murshed, Manzur
- Date: 2011
- Type: Text , Conference paper
- Relation: 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR) p. 3305-3312
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- Description: Variation in viewpoints poses significant challenges to action recognition. One popular way of encoding view-invariant action representation is based on the exploitation of epipolar geometry between different views of the same action. Majority of representative work considers detection of landmark points and their tracking by assuming that motion trajectories for all landmark points on human body are available throughout the course of an action. Unfortunately, due to occlusion and noise, detection and tracking of these landmarks is not always robust. To facilitate it, some of the work assumes that such trajectories are manually marked which is a clear drawback and lacks automation introduced by computer vision. In this paper, we address this problem by proposing view invariant action matching score based on epipolar geometry between actor silhouettes, without tracking and explicit point correspondences. In addition, we explore multi-body epipolar constraint which facilitates to work on original action volumes without any pre-processing. We show that multi-body fundamental matrix captures the geometry of dynamic action scenes and helps devising an action matching score across different views without any prior segmentation of actors. Extensive experimentation on challenging view invariant action datasets shows that our approach not only removes long standing assumptions but also achieves significant improvement in recognition accuracy and retrieval.