List of Titles

Effective and efficient contour-based corner detectors

- Teng, Shyh, Najmus Sadat, Rafi, Lu, Guojun

Authors: Teng, Shyh , Najmus Sadat, Rafi , Lu, Guojun
Date: 2015
Type: Text , Journal article
Relation: Pattern Recognition Vol. 48, no. 7 (2015), p. 2185-2197
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Description: Corner detection is an essential operation in many computer vision applications. Among the contour-based corner detectors in the literature, the Chord-to-Point Distance Accumulation (CPDA) detector is reported to have one of the highest repeatability in detecting robust corners and the lowest localization error. However, based on our analysis, we found that the CPDA detector often fails to accurately detect the true corners when a curve has multiple corners but the sharpness of one or a few of them is much more prominent than the rest. This detector also might not perform well when the corners are closely located. Furthermore, the CPDA detector is also computationally very expensive. To overcome these weaknesses, we propose two effective and efficient corner detectors using simple triangular theory and distance calculation. Our experimental results show that our proposed detectors outperform CPDA and nine other existing corner detectors in terms of repeatability. Our proposed detectors also have a relatively low or comparable localization error and are computationally more efficient. © 2015 Elsevier Ltd.

Video driven traffic modelling in paramics

- Zhou, Hailing, Creighton, Douglas, Lim, Cheepeng, Wei, Lei, Gao, David

Authors: Zhou, Hailing , Creighton, Douglas , Lim, Cheepeng , Wei, Lei , Gao, David
Date: 2013
Type: Text , Conference paper
Relation: Proceedings - UKSim 15th International Conference on Computer Modelling and Simulation, UKSim 2013 p. 525-530
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Description: With urbanization and vehicle availability, there exist many traffic problems including congestion, environmental impact and safety. In order to address these problems, we propose a video driven traffic modelling system in this paper. The system can simulate real-world traffic activities in a computer, based on traffic data recorded in videos. Video processing is employed to estimate metrics such as traffic volumes. These metrics are used to update the traffic system model, which is then simulated using the ParamicsTM traffic simulation platform. Video driven traffic modelling has widespread potential application in traffic systems, due to the convenience and reduced costs of model development and maintenance. Experiments are conducted in this paper to demonstrate the effectiveness of the proposed system. Â© 2013 IEEE.
Description: 2003011214

On temporal order invariance for view-invariant action recognition

- Ul-Haq, Anwaar, Gondal, Iqbal, Murshed, Manzur

Authors: Ul-Haq, Anwaar , Gondal, Iqbal , Murshed, Manzur
Date: 2013
Type: Text , Journal article
Relation: IEEE Transactions on Circuits and Systems for Video Technology Vol. 23, no. 2 (2013), p. 203-211
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Description: View-invariant action recognition is one of the most challenging problems in computer vision. Various representations are being devised for matching actions across different viewpoints to achieve view invariance. In this paper, we explore the invariance property of temporal order of action instances during action execution and utilize it for devising a new view-invariant action recognition approach. To ensure temporal order during matching, we utilize spatiotemporal features, feature fusion and temporal order consistency constraint. We start by extracting spatiotemporal cuboid features from video sequences and applying feature fusion to encapsulate within-class similarity for the same viewpoints. For each action class, we construct a feature fusion table to facilitate feature matching across different views. An action matching score is then calculated based on global temporal order constraint and number of matching features. Finally, the action label of the class with the maximum value of the matching score is assigned to the query action. Experimentation is performed on multiple view Inria Xmas motion acquisition sequences and West Virginia University action datasets, with encouraging results, that are comparable to the existing view-invariant action recognition techniques.

Action-02MCF : A robust space-time correlation filter for action recognition in clutter and adverse lighting conditions

- Ulhaq, Anwaar, Yin, Xiaoxia, Zhang, Yunchan, Gondal, Iqbal

Authors: Ulhaq, Anwaar , Yin, Xiaoxia , Zhang, Yunchan , Gondal, Iqbal
Date: 2016
Type: Text , Conference proceedings , Conference paper
Relation: 17th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2016; Lecce, Italy; 24th-27th October 2016; published in Advanced Conepts for Intelligent Vision Systems (Lecture Notes in Computer Science series) Vol. 10016 LNCS, p. 465-476
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Description: Human actions are spatio-temporal visual events and recognizing human actions in different conditions is still a challenging computer vision problem. In this paper, we introduce a robust feature based space-time correlation filter, called Action-02MCF (0’zero-aliasing’ 2M’ Maximum Margin’) for recognizing human actions in video sequences. This filter combines (i) the sparsity of spatio-temporal feature space, (ii) generalization of maximum margin criteria, (iii) enhanced aliasing free localization performance of correlation filtering using (iv) rich context of maximally stable space-time interest points into a single classifier. Its rich multi-objective function provides robustness, generalization and recognition as a single package. Action-02MCF can simultaneously localize and classify actions of interest even in clutter and adverse imaging conditions. We evaluate the performance of our proposed filter for challenging human action datasets. Experimental results verify the performance potential of our action-filter compared to other correlation filtering based action recognition approaches. © Springer International Publishing AG 2016.
Description: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Object analysis with visual sensors and RFID

- Karmakar, Gour, Karmakar, Nemai, Dooley, Laurence, Kamruzzaman, Joarder

Authors: Karmakar, Gour , Karmakar, Nemai , Dooley, Laurence , Kamruzzaman, Joarder
Date: 2013
Type: Text , Book chapter
Relation: Image Processing: Concepts, Methodologies, Tools, and Applications p. 1492-1507
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Description: Object analysis using visual sensors is one of the most important and challenging issues in computer vision research due principally to difficulties in object representation, segmentation, and recognition within a general framework. This has motivated researchers to investigate exploiting the potential identification capability of RFID (radio frequency identification) technology for object analysis. RFID however, has a number of fundamental limitations including a short sensing range, missing tag detection, not working for all objects, and some items being just too small to be tagged. This has meant applying RFID alone has not been entirely effective in computer vision applications. To address these restrictions, object analysis approaches based on a combination of visual sensors and RFID have recently been successfully introduced. This chapter presents a contemporary review on these object analysis techniques for localisation, tracking, and object and activity recognition, together with some future research directions in this burgeoning field. © 2013, IGI Global.

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.

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