#Cover panorama video registration#

The mpeg-dash standard for multimedia streaming over the internet. of ACM International Conference on Multimedia (MM'16), OSSC paper. OpenVQ: a video quality assessment toolkit. Very deep convolutional networks for large-scale image recognition. of ACM International Conference on Multimedia (MM'13). Video streaming with interactive pan/tilt/zoom. of IEEE International Conference on Image Processing (ICIP'09). Pre-fetching based on video analysis for interactive region-of-interest streaming of soccer sequences. In IEEE International Symposium on Mixed and Augmented Reality. A Framework to Evaluate Omnidirectional Video Coding Schemes. of the International Joint Conference on Artificial Intelligence.

#Cover panorama video registration#

An iterative image registration technique with an application to stereo vision. of IEEE Global Conference on Consumer Electronics (GCCE'12). Mobile and multi-device interactive panorama video distribution system. Signal Processing: Image Communication 51 (2017), 13-25. A comparative study for feature integration strategies in dynamic saliency estimation. In IEEE International Conference on Computer Vision (ICCV'09). ACM Transactions on Multimedia Computing, Communications, and Applications 10, 1 (2014). GamingAnywhere: The First Open Source Cloud Gaming System. Chun-Ying Huang, Kuan-Ta Chen, De-Yu Chen, Hwai-Jung Hsu, and Cheng-Hsin Hsu.of ACM international workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV'12). On tile assignment for region-of-interest video streaming in a wireless LAN. Tiling in Interactive Panoramic Video: Approaches and Evaluation. Transactions on Visualization and Computer Graphics 20, 4 (2014), 616-625. Measuring latency in virtual environments. In International Conference on Pattern Recognition (ICPR'16). A Deep Multi-Level Network for Saliency Prediction. Performance measurements of virtual reality systems: Quantifying the timing and positioning accuracy. of IEEE International Conference on Image Processing (ICIP'16). Transfer learning with deep networks for saliency prediction in natural video. of International Conference on Computational Statistics (COMPSTAT'10). Large-scale machine learning with stochastic gradient descent. of IEEE International Conference on Multimedia and Expo (ICME'16). Understanding spatial correlation in eye-fixation maps for visual attention in videos. Augmented Virtual Reality revenue forecast revised to hit $120 billion by 2020. Trace-driven simulation results show the merits of our proposed fixation prediction networks compared to the existing solutions, including: (i) lower consumed bandwidth, (ii) shorter initial buffering time, and (iii) short running time. We then train and validate two design alternatives of our proposed networks, which allows us to identify the better-performing design with the optimal parameter settings. We build a 360В° video streaming testbed to HMDs, and recruit twenty-five viewers to watch ten 360В° videos. The sensor-related features include HMD orientations, while the content-related features include image saliency maps and motion maps. In this paper, we develop fixation prediction networks that concurrently leverage sensor- and content-related features to predict the viewer fixation in the future, which is quite different from the solutions in the literature. Existing solutions either use the viewer's current orientation to approximate the FoVs in the future, or extrapolate future FoVs using the historical orientations and dead-reckoning algorithms. We study the problem of predicting the Field-of-Views (FoVs) of viewers watching 360В° videos using commodity Head-Mounted Displays (HMDs).