Current Issue : October - December Volume : 2018 Issue Number : 4 Articles : 5 Articles
Speaking of roadmaintenance, the preventivemaintenance strategy is preferable for most governments.Many governments possess\nspecial vehicles that can accurately detect and classify many types of road distresses. By running these vehicles frequently, small\nroad distresses will be detected before growing into the big ones.However, because running these huge and expensive vehicles is not\neasy, in practical, it usually ends up with infrequent road inspection regardless of having automatic road inspection vehicles. In this\npaper, we focus on investigating and developing an automatic and nondestructive visual inspection system whose setup and usage\nare designed by considering the context of drivers, driving styles, and road conditions in Bangkok, the capital city of Thailand. Our\nproposal includes a workflow diagram of a vision-based road inspection system that is capable of detecting, classifying, tracking,\nmeasuring, and pricing road distresses. As for the proof-of-concept, our current system focuses on detecting one specific type\nof road distresses called pothole, using only one onboard in-car camera. Experimental results reveal that the context of Bangkok\nintroduces many nontrivial challenges for vision-based analysis systemswheremaintaining both accuracy and ease of use altogether\nmay not be easy....
Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition\nmethods are supposed to have the same camera view during both training and testing. And thus performances of these single-view\napproaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above\nproblem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based\non multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. In the first step,\nsubvolumes of continuous human-centered figures are extracted from original videos. In the next step, spatiotemporal cuboids\nsampled from these subvolumes are characterized by multiple low-level descriptors. Then a set of multitask random forests are\nbuilt upon multiview cuboids sampled at adjacent positions and construct an integrated mid-level representation for multiview\nsubvolumes of one action. Finally, a random forest classifier is employed to predict the action category in terms of the learned\nrepresentation. Experiments conducted on themultiview IXMAS action dataset illustrate that the proposed method can effectively\nrecognize human actions depicted in multiview videos....
A novel method for camera calibration is proposed based on an analysis of lens distortion in camera imaging. In the method, a line\nthrough the centre of concentric circles is used as a template in which orthogonal directions can be determined from an angle of\ncircumference that corresponds to a diameter. By using three lines through the centre of concentric circles, based on the invariance\nof the cross-ratio, an image at the centre of the concentric circles can be used to obtain the vanishing point.The intrinsic parameters\nof the camera can be computed based on the constraints of the orthogonal vanishing points and the imaged absolute conic. Thelens\ndistortion causes points in the template to have a position offset. In the proposedmethod,we optimize the positions of thedistortion\npoints such that they gradually approach those of the ideal points. The simulated and real-world experiments demonstrate that the\nproposed method is efficient and feasible....
After many decades of flourishing computer science it is now rather evident that in a world\ndominated by different kinds of digital information, both applications and people are forced to seek\nnew, innovative structures and forms of data management and organization. Following this blunt\nobservation, researchers in informatics have strived over the recent years to tackle the non-unique\nand rather evolving notion of context, which aids significantly the data disambiguation process.\nMotivated by this environment, this work attempts to summarize and organize in a researcher-friendly\ntabular manner important or pioneer related research works deriving from diverse computational\nintelligence domains: Initially, we discuss the influence of context with respect to traditional low-level\nmultimedia content analysis and search, and retrieval tasks and then we advance to the fields of\noverall computational context-awareness and the so-called human-generated contextual elements.\nIn an effort to provide meaningful information to fellow researchers, this brief survey focuses on\nthe impact of context in modern and popular computing undertakings of our era. More specifically,\nwe focus to the presentation of a short review of visual context modeling methods, followed by\nthe depiction of context-awareness in modern computing. Works dealing with the interpretation of\ncontext by human-generated interactions are also discussed herein, as the particular domain gains an\never-increasing proportion of related research nowadays. We then conclude the paper by providing a\nshort discussion on (i) the motivation behind the included context type categorization into three main\npillars; (ii) the findings and conclusions of the survey for each context category; and (iii) a couple of\nbrief advices derived from the survey for both interested developers and fellow researchers...
3D printing can spur manufacturing rebirth in Nigeria and the World in general.\nThere are many areas where 3D printing is creating significant change,\nparticularly in designing and prototyping of new products, in the arts, and in\nvisualizing abstract concepts. This is a step change from conventional manufacturing\nprocesses to rapid prototyping and layer manufacturing. This report\nhas defined rapid prototyping, rapid manufacturing and the current technologies\navailable to fabricate 3D components. In addition to this, it provides a\nbrief overview of the current contributions of the Edo University Iyamho\n(EUI) in collaboration with the Federal University of Petroleum Resources, to\nsustain manufacturing research initiatives towards the development of locally\nfabricated 3D printer and the possible future Additive Manufacturing in Nigeria.\nIt is anticipated that this work will benefit the Nigerian academic, research\ninstitutes, industries, thus, enhance the GDP contribution of the\nmanufacturing sector in Nigeria....
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