Large scale scene modeling, understanding and synthesis
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MOTSLAM: MOT-assisted monocular dynamic SLAM using single-view depth estimation [2022]
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In this work, we present MOTSLAM, a dynamic visual SLAM system with the monocular configuration that tracks both poses and bounding boxes of dynamic objects.
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Attention based Accident Detection in Dashboard Cameras [2021]
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In this study, we propose a method for estimating accidents from video captured on a drive recorder using a deep learning with attention mechanism. For preprocess, self-annotation method for tracking of moving objects in video was also developed.
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Estimating Sudden Braking using Weather Estimation by a Deep Learning Framework from Drive Recorder Data [2020]
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To analyze the occurrence of sudden braking, we use deep learning to identify emergency braking data using weather estimated from drive recorder video.
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Flooded detection from drive recorder video using deep learning (GAN) [2018--2019]
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We use deep learning, specifically GAN, to extend the data in order to detect the unusual event like flooded scene from drive recorder image sequence.
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City name estimation by larning large image dataset using random forest [2014]
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There are many anonymous on-vehicle video uploaded on the Internet. Our technique can estimate the place where the video is captured by learning based approach using random forest. Since our technique uses not only single image, but also several frames, it is expected to improve accuracy than common techniques. In the experiments, we selected 10 cities and tested to show the effectiveness of our method.
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Efficient On-Vehicle Video Localization by Space-time Matching [2012--2014]
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On-vehicle video localization without GPS is necessary. In our research it is achieved by matching between real data and digital map. To increase the stability and accuracy, space-time feature is extracted from both video data and digital map.
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Photorealistic Wide-Area Real-time Rendering [2012--2013]
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We make photo-realistic wide-area rendering using billboard represents general shape of urban scene captured car-mounted camera. And also we apply PCA compression technique to texture, reconstruct texture on GPU as faster than faster, implement real-time rendering.
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Video synthesis with multiple cameras [2008--2009]
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Like photo-synthesis, 3D Reconstruction of urban scene can be realized by multiple videos captured by car-mounted video cameras.
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Real-time Rendering using Eigen Space Compression [2007--2008]
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We compress the sequence of omni directional image based on IBR(Image Based Rendering),
and render a large scale scene in real-time.
This operation is all linear, and because we run it in the fragment-shader of the graphics card,
real-time rendering is achieved.
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Space-Time Image Analysis [2000--2007]
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This research is about generating and analyzing space-time images by fixing
the image sequence (video) to a time base direction.
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Large scale scene modeling [2000--2009]
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Multiple video cameras are set up on the car, and take real world images in various directions.
The panorama image is generated by integrating multiple images.
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Image based large scale scene rendering [2000--2005]
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Large scale scene rendering is done by IBR/MBR hybrid method using generated panorama images.
Efficient image compression technique is also proposed for image based method, which used geometry.
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