Multi-Resolution Design for Large-Scale and High-Resolution Monitoring

Chen, Kuan-Wen; Lin, Chih‐Wei; Chiu, Tzu-Hsuan; Chen, Mike Yen-Yang; Hung, Yi‐Ping

doi:10.1109/tmm.2011.2165055

Cited by 17 publications

(13 citation statements)

References 21 publications

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“…Existing solutions to preserve the high-resolution detail is either to construct a 3D model of the scene [17] or use a large high-resolution display [18]. Another way is to use a separate output display to render the output of each camera [20]. However, these viewing approaches are impractical to implement for our application.…”

Section: Related Workmentioning

confidence: 99%

Foveation Pipeline for 360° Video-Based Telemedicine

Syawaludin

Lee

Hwang

2020

Sensors

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Pan-tilt-zoom (PTZ) and omnidirectional cameras serve as a video-mediated communication interface for telemedicine. Most cases use either PTZ or omnidirectional cameras exclusively; even when used together, images from the two are shown separately on 2D displays. Conventional foveated imaging techniques may offer a solution for exploiting the benefits of both cameras, i.e., the high resolution of the PTZ camera and the wide field-of-view of the omnidirectional camera, but displaying the unified image on a 2D display would reduce the benefit of “omni-” directionality. In this paper, we introduce a foveated imaging pipeline designed to support virtual reality head-mounted displays (HMDs). The pipeline consists of two parallel processes: one for estimating parameters for the integration of the two images and another for rendering images in real time. A control mechanism for placing the foveal region (i.e., high-resolution area) in the scene and zooming is also proposed. Our evaluations showed that the proposed pipeline achieved, on average, 17 frames per second when rendering the foveated view on an HMD, and showed angular resolution improvement on the foveal region compared with the omnidirectional camera view. However, the improvement was less significant when the zoom level was 8× and more. We discuss possible improvement points and future research directions.

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Section: Related Workmentioning

confidence: 99%

Foveation Pipeline for 360° Video-Based Telemedicine

Syawaludin

Lee

Hwang

2020

Sensors

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“…The foveation process can be performed by means of software downsampling [14], with reduced sampling [19] for systems that use at least two cameras [20,21]. Each type of execution of the foveation process has its relevant advantages and disadvantages.…”

Section: Background Theorymentioning

confidence: 99%

Efficient 3D Objects Recognition Using Multifoveated Point Clouds

Oliveira

Souza

Fernandes

et al. 2018

Sensors

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Technological innovations in the hardware of RGB-D sensors have allowed the acquisition of 3D point clouds in real time. Consequently, various applications have arisen related to the 3D world, which are receiving increasing attention from researchers. Nevertheless, one of the main problems that remains is the demand for computationally intensive processing that required optimized approaches to deal with 3D vision modeling, especially when it is necessary to perform tasks in real time. A previously proposed multi-resolution 3D model known as foveated point clouds can be a possible solution to this problem. Nevertheless, this is a model limited to a single foveated structure with context dependent mobility. In this work, we propose a new solution for data reduction and feature detection using multifoveation in the point cloud. Nonetheless, the application of several foveated structures results in a considerable increase of processing since there are intersections between regions of distinct structures, which are processed multiple times. Towards solving this problem, the current proposal brings an approach that avoids the processing of redundant regions, which results in even more reduced processing time. Such approach can be used to identify objects in 3D point clouds, one of the key tasks for real-time applications as robotics vision, with efficient synchronization allowing the validation of the model and verification of its applicability in the context of computer vision. Experimental results demonstrate a performance gain of at least 27.21% in processing time while retaining the main features of the original, and maintaining the recognition quality rate in comparison with state-of-the-art 3D object recognition methods.

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“…The results demonstrated that the completion time with the DF+C was significantly shorter than that with the fixed F+C. Chen et al [18] proposed using a DF+C display system in visual surveillance applications and evaluated its feasibility. The user study results showed that for visual monitoring tasks, the DF+C approach was significantly faster than existing approaches and was preferred by users.…”

Section: Related Workmentioning

confidence: 99%

Reducing Motion Blur Artifact of Foveal Projection for a Dynamic Focus-Plus-Context Display

Iwai

Kodama

Sato

2015

IEEE Trans. Circuits Syst. Video Technol.

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This paper presents a novel technique to reduce the motion blur artifacts of foveal projection in a dynamic focus-pluscontext (DF+C) display. The DF+C display is generally configured with multiple projectors and provides a nonuniform spatial resolution that consists of high-resolution (hi-res) regions (foveal projection) and low-resolution regions (peripheral projection). A serious problem of the DF+C display is motion blur, which inevitably occurs when a foveal projection is moved by a pan-tilt mirror or gantry. We propose a solution that reduces the motion blur artifacts, and evaluate how this solution improves the image quality using both qualitative and quantitative experiments. Our proposed method defines an error function to assess the displayed image quality as the difference between an original hi-res image and the displayed image by considering the nonuniform spatial property of human visual acuity. Then, it decides the set of positions and moving techniques of foveal projections so that the sum of errors during a video sequence is minimized. Through experiment, we confirmed that the proposed method can provide a better image quality and significantly improve the motion blur artifacts when compared with a conventional DF+C display.

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Multi-Resolution Design for Large-Scale and High-Resolution Monitoring

Cited by 17 publications

References 21 publications

Foveation Pipeline for 360° Video-Based Telemedicine

Foveation Pipeline for 360° Video-Based Telemedicine

Efficient 3D Objects Recognition Using Multifoveated Point Clouds

Reducing Motion Blur Artifact of Foveal Projection for a Dynamic Focus-Plus-Context Display

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