List of Titles

Detection of multiple dynamic textures using feature space mapping

- Rahman, Ashfaqur, Murshed, Manzur

Authors: Rahman, Ashfaqur , Murshed, Manzur
Date: 2009
Type: Text , Journal article
Relation: IEEE Transactions on Circuits and Systems for Video Technology Vol. 19, no. 5 (2009), p. 766-771
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Description: Abstract— Image sequences of smoke, fire, etc. are known as dynamic textures. Research is mostly limited to characterization of single dynamic textures. In this paper we address the problem of detecting the presence of multiple dynamic textures in an image sequence by establishing a correspondence between the feature space of dynamic textures and that of their mixture in an image sequence. Accuracy of our proposed technique is both analytically and empirically established with detection experiments yielding 92.5% average accuracy on a diverse set of dynamic texture mixtures in synthetically generated as well as real-world image sequences.

A hybrid object detection technique from dynamic background using Gaussian mixture models

- Haque, Mohammad, Murshed, Manzur, Paul, Manoranjan

Authors: Haque, Mohammad , Murshed, Manzur , Paul, Manoranjan
Date: 2008
Type: Text , Conference paper
Relation: 2008 IEEE 10th Workshop on Multimedia Signal Processing p. 915-920
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Description: Adaptive background modelling based object detection techniques are widely used in machine vision applications for handling the challenges of real-world multimodal background. But they are constrained to specific environment due to relying on environment specific parameters, and their performances also fluctuate across different operating speeds. On the other side, basic background subtraction (BBS) is not suitable for real applications due to manual background initialization requirement and its inability to handle repetitive multimodal background. However, it shows better stability across different operating speeds and can better eliminate noise, shadow, and trailing effect than adaptive techniques as no model adaptability or environment related parameters are involved. In this paper, we propose a hybrid object detection technique for incorporating the strengths of both approaches. In our technique, Gaussian mixture models (GMM) is used for maintaining an adaptive background model and both probabilistic and basic subtraction decisions are utilized for calculating inexpensive neighbourhood statistics for guiding the final object detection decision. Experimental results with two benchmark datasets and comparative analysis with recent adaptive object detection technique show the strength of the proposed technique in eliminating noise, shadow, and trailing effect while maintaining better stability across variable operating speeds.

Dynamic texture synthesis using motion distribution statistics

- Rahman, Ashfaqur, Murshed, Manzur

Authors: Rahman, Ashfaqur , Murshed, Manzur
Date: 2008
Type: Text , Journal article
Relation: Journal of Research and Practice in Information Technology Vol. 40, no. 2 (2008), p. 129-148
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Description: n this paper we propose a motion based approach for synthesizing dynamic textures. Dynamic textures are natural phenomenon characterized by their distinctive motion patterns. Synthesis of these textures is thus considered as the regeneration of a motion pattern that has identical motion distribution of a source texture. In this paper we propose a synthesis technique where new textures are generated by computing their movement pattern from a known motion distribution followed by the generation of image frames. Experimental results demonstrate the ability of the proposed technique by producing visually promising dynamic textures.

Improved Gaussian mixtures for robust object detection by adaptive multi-background generation

- Haque, Mohammad, Murshed, Manzur, Paul, Manoranjan

Authors: Haque, Mohammad , Murshed, Manzur , Paul, Manoranjan
Date: 2008
Type: Text , Conference paper
Relation: 19th International Conference on Pattern Recognition p. 1-4
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Description: Adaptive Gaussian mixtures are widely used to model the dynamic background for real-time object detection. Recently the convergence speed of this approach is improved and a relatively robust statistical framework is proposed by Lee (PAMI, 2005). However, object quality still remains unacceptable due to poor Gaussian mixture quality, susceptibility to background/foreground data proportion, and inability to handle intrinsic background motion. This paper proposes an effective technique to eliminate these drawbacks by modifying the new model induction logic and using intensity difference thresholding to detect objects from one or more believe-to-be backgrounds. Experimental results on two benchmark datasets confirm that the object quality of the proposed technique is superior to that of Leepsilas technique at any model learning rate.

On stable dynamic background generation technique using Gaussian mixture models for robust object detection

- Haque, Mohammad, Murshed, Manzur, Paul, Manoranjan

Authors: Haque, Mohammad , Murshed, Manzur , Paul, Manoranjan
Date: 2008
Type: Text , Conference paper
Relation: 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance p. 41-48
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Description: Gaussian mixture models (GMM) is used to represent the dynamic background in a surveillance video to detect the moving objects automatically. All the existing GMM based techniques inherently use the proportion by which a pixel is going to observe the background in any operating environment. In this paper we first show that such a proportion not only varies widely across different scenarios but also forbids using very fast learning rate. We then propose a dynamic background generation technique in conjunction with basic background subtraction which detected moving objects with improved stability and superior detection quality on a wide range of operating environments in two sets of benchmark surveillance sequences.

Optimal arbitrary shaped pattern-based video coding

- Paul, Manoranjan, Murshed, Manzur

Authors: Paul, Manoranjan , Murshed, Manzur
Date: 2008
Type: Text , Conference paper
Relation: 2008 IEEE 10th Workshop on Multimedia Signal Processing p. 206-211
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Description: Very low bit-rate video coding algorithms using content-based generated patterns to segment out moving regions at macroblock level have exhibited good potential for improved coding efficiency when embedded into the H.264 standard as extra mode. This content-based pattern generation (CPG) algorithm provides local optimal result as only one pattern can be optimally generated from a given set of moving regions. But, it failed to provide optimal results for multiple patterns from entire sets. Obviously, a global optimal solution for clustering the set and then generation of multiple patterns enhances the performance farther. But a global optimal solution is not achievable due to the non-polynomial nature of the clustering problem. In this paper, we proposed a near optimal content-based pattern generation (OCPG) algorithm which outperforms the existing approach. Coupling OCPG, generating a set of patterns after clustering the macroblocks into several disjoint sets, with direct pattern selection algorithm by allowing all the macroblocks in multiple pattern modes outperforms the existing pattern-based coding while both embedded into the H.264.

Performance evaluation of multipath cellular networks in obstacle mobility model for downlink packet video communication

- Al Yusuf, Abdullah, Murshed, Manzur

Authors: Al Yusuf, Abdullah , Murshed, Manzur
Date: 2008
Type: Text , Conference paper
Relation: 2008 IEEE 68th Vehicular Technology Conference p. 1-5
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Description: Obstacles present in the line of sight transmission path of a wireless signal severely attenuates the received signal power. Extreme fluctuations of the received signal power caused by shadowing can create "blind spots". Blind spots are areas within the cellular coverage area from where no communication is possible to the base station (BS). For single path packet based services link failures results in total loss of communication. The problem of link failure and blind spots can almost be eliminated in the recently proposed multipath cellular architecture (MCA) which provisions up to three different communication links from the mobile node (MN) to three adjacent BSs through overlapped coverage. Voice and/or multimedia packet delivery can thus benefit by establishing communication from the best interface in terms of received signal power. In this paper, we evaluate the performance of the multi-path MCA model in reducing link failure and blind spot communication problems in presence of multiple obstacles and shadow fading. Obstacle mobility model is utilized as the preferred user mobility model. Video transmission performance improves significantly in terms of reduced packet loss and improved reproduced signal quality at the receiver for the multipath MCA model compared to the existing single path cellular network architecture

Temporal texture characterization : A review

- Rahman, Ashfaqur, Murshed, Manzur

Authors: Rahman, Ashfaqur , Murshed, Manzur
Date: 2008
Type: Text , Book chapter
Relation: Computational Intelligence in Multimedia Processing: Recent Advances p. 291-316
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Description: Summary. A large class of objects commonly experienced in a real world scenario exhibits characteristic motion with certain form of regularities. Contemporary literature coined the term “temporal texture”1 to identify image sequences of such motion patterns that exhibit spatiotemporal regularity. The study of temporal textures dates back to the early nineties. Many researchers in the computer vision community have formulated techniques to analyse temporal textures. This chapter aims to provide a comprehensive literature survey of the existing temporal texture characterization technique

Threshold-free pattern-based low bit rate video coding

- Paul, Manoranjan, Murshed, Manzur

Authors: Paul, Manoranjan , Murshed, Manzur
Date: 2008
Type: Text , Conference paper
Relation: 2008 15th IEEE International Conference on Image Processing p. 1584-1587
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Description: Pattern-based video coding (PVC) has already established its superiority over recent video coding standard H.264, at low bit rate because of an extra pattern-mode to segment out the arbitrary shape of the moving region within the macroblock (MB). To determine the pattern-mode, the PVC however uses three thresholds to reduce the number of MBs coded using the pattern- mode. By setting these content-sensitive thresholds to any predefined values, the technique risks ignoring some MBs that would otherwise be selected by the rate-distortion optimization function for this mode. Consequently, the ultimate achievable performance is sacrificed to save motion estimation times. In this paper, a novel PVC scheme is proposed by removing all thresholds to determine this mode and hence more efficient performance is achieved without knowing the content of the video sequences. To keep computational complexity in check, pattern motion is approximated from the motion vector of the MB. In addition, efficient pattern similarity metric and new Lagrangian multipliers are also developed. The experimental results confirm that this new scheme improves the image quality by at least 0.5 dB and 1.0 dB compared to the existing PVC and the H.264 respectively

Prefix coding of integers with real-valued predictions using cosets

- Ali, Mortuza, Murshed, Manzur

Authors: Ali, Mortuza , Murshed, Manzur
Date: 2007
Type: Text , Journal article
Relation: IEEE Communications Letters, vol. 11, no. 10, IEEE Communications Society, p. 814-816
Full Text: false
Description: In predictive coding of integers real-valued residuals are mapped to integers before encoding, leaving room for improvement by reducing the loss due to rounding. In this paper, we propose a new prefix coding scheme where actual integer values, instead of the residuals, are encoded using cosets with real domain predictions as the side information. This novel coding scheme outperforms Golomb-based coding by reducing the rounding loss with similar computational and memory complexity.

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