Showing papers by "Muhammad Abbas published in 2017"
TL;DR: The OT parameters are optimized using particle swarm optimization with respect to two different cost functions to achieve the best possible result for each scenario.
Abstract: Advanced correlation filters are an effective tool for target detection within a particular class. Most correlation filters are derived from a complex filter equation leading to a closed form filter solution. The response of the correlation filter depends upon the selected values of the optimal trade-off (OT) parameters. In this paper, the OT parameters are optimized using particle swarm optimization with respect to two different cost functions. The optimization has been made generic and is applied to each target separately in order to achieve the best possible result for each scenario. The filters obtained using standard particle swarm optimization (PSO) and hierarchal particle swarm optimization algorithms have been compared for various test images with the filter solutions available in the literature. It has been shown that optimization improves the performance of the filters significantly.
13 citations
TL;DR: Experimental results show that the proposed visualization technique produces promising results and found effective in conveying meaningful information while alleviating the need of searching exhaustively colossal amount of video data.
Abstract: Video visualization (VV) is considered to be an essential part of multimedia visual analytics. Many challenges have arisen from the enormous video content of cameras which can be solved with the help of data analytics and hence gaining importance. However, the rapid advancement of digital technologies has resulted in an explosion of video data, which stimulates the needs for creating computer graphics and visualization from videos. Particularly, in the paradigm of smart cities, video surveillance as a widely applied technology can generate huge amount of videos from 24/7 surveillance. In this paper, a state of the art algorithm has been proposed for 3D conversion from traffic video content to Google Map. Time-stamped glyph-based visualization is used effectively in outdoor surveillance videos and can be used for event-aware detection. This form of traffic visualization can potentially reduce the data complexity, having holistic view from larger collection of videos. The efficacy of the proposed scheme has been shown by acquiring several unprocessed surveillance videos and by testing our algorithm on them without their pertaining field conditions. Experimental results show that the proposed visualization technique produces promising results and found effective in conveying meaningful information while alleviating the need of searching exhaustively colossal amount of video data.
10 citations
01 Dec 2017
TL;DR: This paper presents a novel technique which merges a very efficient recognition and tracking procedures and results are very efficient and fast tracking of object in subsequent frames.
Abstract: Recognition and Tracking of Images is still one of the most sought after areas in the field of Image Processing mainly because of applications and presentations associated with it Recognition of objects in a crowded and occluded environment is very challenging task as all the other objects besides the object of interest acts as noise Other challenges associated with recognition and Tracking is the ever changing coordinates of the object during the tracking procedure In this paper both the above mentioned challenges have been addressed using a novel technique which merges a very efficient recognition and tracking procedures First recognition of image is done using modified Maximum Average Correlation Filter (MACH) which will identify the two dimensional coordinates of the object if interest in a secluded environment The coordinates are then updated using a Proximal Gradient (PG) filter which uses Particle Filter as for systematic and periodic updation of images recursively Proximal Gradient Filter uses the random variables and their posterior distribution for efficient prediction of coordinates of object of interest End result is very efficient and fast tracking of object in subsequent frames
7 citations
TL;DR: In this article, a comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out for different types of target distortions and the zero-aliasing Maximum Average Correlation Height (MACH) filter has been identified as the best choice based on their research for achieving enhanced results in the presence of any type of variance.
Abstract: Correlation filters are a well established means for target recognition tasks. However, the unintentional effect of circular
correlation has a negative influence on the performance of correlation filters as they are implemented in frequency
domain. The effects of aliasing are minimized by introducing zero aliasing constraints in the template and test image. In
this paper, the comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out
for different types of target distortions. The zero aliasing Maximum Average Correlation Height (MACH) filter has been
identified as the best choice based on our research for achieving enhanced results in the presence of any type of variance
which are discussed in results section. The reformulation of the MACH expressions with zero aliasing has been made to
demonstrate the achievable enhancement to the logarithmic MACH filter in target detection applications.
5 citations
01 Dec 2017
TL;DR: The cluster based scheme is designed in such a way that the AAGVs protocol can adapt itself in real time without affecting its performance by maintaining stable Inter-Vehicular Communication (IVC) links.
Abstract: The Autonomous Ground Vehicles (AGVs) are developed to perform the rescue operations independently for providing safety to human lives such as in mines detection and clearance operations. The performance of these AGVs has been enhanced in our previous work by implementing the Vehicular Ad Hoc Network (VANET) among these vehicles. In this piece of research, the Autonomous Aerial and Ground Vehicles (AAGVs) routing protocol has been proposed, in which the aerial vehicles are introduced to overcome the limitations of AGVs communication for disseminating the Mines Detection Messages (MDMs). Additionally, the cluster based scheme is designed in such a way that the AAGVs protocol can adapt itself in real time without affecting its performance by maintaining stable Inter-Vehicular Communication (IVC) links. The simulation of the proposed protocol in Network Simulator illustrates that the delay and overhead have been reduced. On the other hand, the packet delivery ratio and throughput have been increased by adopting the multicast communication approach.
3 citations
01 Dec 2017
TL;DR: Most required expertise and skills are identified and what type of skills should employees have according to their role in the organization are identified.
Abstract: Good skills and expertise of employees in an organization are the key factors for producing the quality products and completing projects successfully. Keeping the skills and knowledge of employees updated is one of the toughest and challenging tasks of the project management process. In developing countries like Pakistan, this task becomes more challenging due to lack of training and skill building institutes. The factors like changes in technology and increased demand for rapid development are addressed in this paper. Most required expertise and skills are identified. Our team has collected data by filling the questionnaires from IT professionals working on different projects in different organizations of the country. All expertise are divided into two main categories technical expertise or skills and non-technical / soft skills. Then characterized these skills according to the roles of employees. Finally, analysis of the whole data is performed by the statistical software like the SPSS and the Minitab, to find out which are the significant expertise and skills which really affects the performance of software organizations. We also identified what type of skills should employees have according to their role in the organization. The information developed by conducting this study is useful for many stakeholders in the local perspective, including professionals, project managers, and the Pakistan Software Export Board.
1 citations
01 Dec 2017
TL;DR: The research proposes a systematic testing technique which uses Factor Interdependency Graphs (FIG) to test the product lines in order to ensure early defect detection, fault correction and to find common set of testing assets for the subsequent products of the SPL.
Abstract: SPL (Software Product Line) is known as a set of software systems that share mutual set of features. These features are developed from core assets in a commended way. Testing plays a significant role in ensuring quality of software product for their reuse in future to reduce the development time and extensive testing of the similar product persistently. Testing a product line is very tricky and challenging. It has gained reflectivity in the development process as quality issues are rising significantly for software development organizations. The research proposes a systematic testing technique which uses Factor Interdependency Graphs (FIG) to test the product lines in order to ensure early defect detection, fault correction and to find common set of testing assets for the subsequent products of the SPL.