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Computation of Visual Rear Ground Clearance of vehicles is an important computer vision application. This problem is challenging as the road and vehicle rear bumper may have subtle appearance differences, vehicle motion is on uneven surfaces and there are real-time considerations. In this paper a method is presented to compute the Visual Rear Ground Clearance of a vehicle from its rear view video...
In this paper, by using geodesic distance and compactness prior, we present some effective improvements concerning the two important aspects of diffusion-based methods: the construction of the diffusion matrix and seed vector. First, based on the geodesic distance, we construct a 2-layer knn graph. Compared with the most frequently used 2-layer neighborhood graph, our graph does not only effectively...
With the fast development of Chinese high-speed railway, the operation safety of locomotives has attracted great attention of railway departments. As an important detection aspect of locomotive safety, the locomotive bottom has lot of insecurity factors, and faults of running gear are the most direct factor affecting the safe operation of locomotives. Generally, the traditional method is extremely...
In this work, we present a full-reference stereo image quality assessment algorithm that is based on the sparse representations of luminance images and depth maps. The primary challenge lies in dealing with the sparsity of disparity maps in conjunction with the sparsity of luminance images. Although analysing the sparsity of images is sufficient to bring out the quality of luminance images, the effectiveness...
Visual Inspection is an essential part in the quality control in electronic manufacturing industry, especially in PCB assembly processes. With the advance of surface mount technology as a means to increase automation level in electronic assembly line, with production volume achieving thousands of board per day, manual visual inspection becomes increasingly prohitive. For this purpose, Automatic Optical...
Developing effective fusion schemes for multiple feature types has always been a hot issue in content-based image retrieval. In this paper, we propose a novel method for graph based visual reranking, which addresses two major limitations in existing methods. Firstly, in the phase of graph construction, our method introduces fine-grained measurements for image relations, by assigning the edge weights...
The social insect metaphor for solving problems has become an emerging topic in the recent years emphasizing on stochastic construction practice, building the key probabilistically to optimize the solution related to any kind of a problem. As we are aware that image makes the human visualize the existence of entities in nature and helps individual to get the feel of the services without solely relying...
To fully exploit the potential of today's computers, application developers need to design for concurrency. Along with parallel execution new performance problems emerge. Developers gain insight into application behavior by visualizing inter-process communication in timelines. They use this insight to eliminate performance bottlenecks. Timeline visualizations overlay function call structure with communication...
AprilTags and other passive fiducial markers require specialized algorithms to detect markers among other features in a natural scene. The vision processing steps generally dominate the computation time of a tag detection pipeline, so even small improvements in marker detection can translate to a faster tag detection system. We incorporated lessons learned from implementing and supporting the AprilTag...
Natural images follow statistics inherited by the structure of our physical (visual) environment. In particular, a prominent facet of this structure is that images can be described by a relatively sparse number of features. We designed a sparse coding algorithm biologically-inspired by the architecture of the primary visual cortex. We show here that coefficients of this representation exhibit a power-law...
We introduce a new algorithm for contour detection including the identification of corners and T-junctions. The proposed model is inspired by the early stages of the mammal visual system. This strategy incorporates the detection of corners and T-junctions as part of the process interacting with contour detection.
In this paper, we propose a scene clustering algorithm which uses straight line features. Scenes are represented as nodes in the graph, and each connectivity between nodes is calculated by a pre-trained vocabulary tree. By applying a spectral clustering algorithm to the constructed graph, the scenes are partitioned into k groups where k is determined by the proposed estimation method. Instead of using...
Visually salient object or region detection in images is an active research field in recent years. Inspired by that curvelets can provide multi-scale sparse representation of objects with edges and textures, in this paper, we propose a novel saliency detection model based on fast discrete curvelet transform (SDCT) to detect more compact salient objects in an image. First, fast discrete curvelet transform...
The detection of consistent feature points in an image is fundamental for various kinds of computer vision techniques, such as stereo matching, object recognition, target tracking and optical flow computation. This paper presents an event-based approach to the detection of corner points, which benefits from the high temporal resolution, compressed visual information and low latency provided by an...
salient regions detection is a very popular topic in pattern recognition. A novel method was presented to detect salient regions using color volume and edge in the manner of simulating visual attention mechanism. In order to detect salient regions, we have combined color volume and edge cues together and used them as the primary visual features. Color and edge are important cues that attract human's...
Subpixel edge detection is critical in three-dimension computer-assisted intra-operative navigation based on a marker-based matching technique, because it significantly influences the accuracy of guidance. In order to increase the accuracy, a gray moment based method is proposed to extract the accurate contours of the connected areas. Firstly, a border following algorithm is used to acquire a rough...
This paper describes a method of image sharpness evaluation while taking into account the photographer's aesthetic intention. The main idea is utilizing a visual importance map that estimates the weight of each pixel to guild evaluating image sharpness. The visual importance map is computed automatically with a saliency detection algorithm based on global color contrast. Our technique allows to treat...
Data centers are extremely important facilities that contain core business information and applications, but the energy consumption is an inevitable issue, so the thermal distribution monitoring is critical for data centers reliable and stable operation. Thermal information enables monitoring and autonomic thermal management in large data centers. Recent approaches that employed a mobile robot or...
Medical imaging systems often require image enhancement to visualize images of the human body and its organs. This would help medical professionals in irregularity or abnormality detection and diagnosis. This paper demonstrates a method to enhance medical related images. The proposed algorithm uses techniques, such as, guided filtering, edge enhancement, contrast stretching, and image fusion to enhance...
This paper presents automated navigation control of an Unmanned Aerial Vehicle (UAV) based on visual data gathered by onboard camera. With depletion of easy resources and health, safety and environmental (HSE) challenges in exploiting newly found resources in hostile conditions are forcing oil and gas companies to look for robotic solutions for their problems. Pipelines carrying inflammable and toxic...
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