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Tanaka Y.,NTT Media Intelligence Laboratories | Ochi D.,NTT Media Intelligence Laboratories
NTT Technical Review

Video technology is becoming more sophisticated, and the amount of available content is increasing substantially. Accordingly, individual preferences for video content are becoming more diverse. We have perceived a need for a means of personalized viewing that enables viewers to select their preferred subjects and scenes within the content rather than just passively selecting video content created by third parties, as in the conventional style. This article introduces a system that partitions 4K video into tiles, compresses it, and enables only parts selected by the viewer within the video to be distributed live at the desired size and with high quality. Source

Niigaki H.,NTT Media Intelligence Laboratories | Shimamura J.,NTT Media Intelligence Laboratories | Kojima A.,NTT Media Intelligence Laboratories
Proceedings - 2015 International Conference on 3D Vision, 3DV 2015

We present a new unsupervised technique to segment 3D Lidar points in outdoor environments. The main idea of this work is to identify artificial objects according to the existence of extruded shapes. Many artificial objects are composed of extruded shapes such as cylinders, planes, cubes, and lines. Therefore, we detect these arbitrarily extruded shapes on the basis of an indicator for repetitive crosssection shapes, and connect the components according to the strength between the overlapping areas in the extruded surfaces. Conventional segmentation methods that use local geometry information may sometimes produce erroneous results in scenes where there are many objects that are very near to and partially in contact with each other. In contrast, our method is more robust against these complex scenes using large scale surface overlapping strength. Experiments show it provides good results in urban environments and expressway scenes. © 2015 IEEE. Source

Imoto K.,NTT Media Intelligence Laboratories | Ohishi Y.,NTT Communication Science Laboratories | Uematsu H.,NTT Media Intelligence Laboratories | Ohmuro H.,NTT Media Intelligence Laboratories
IEEE International Workshop on Machine Learning for Signal Processing, MLSP

We propose a model for analyzing acoustic scenes by using long-term (more than several seconds) acoustic signals based on a probabilistic generative model of an acoustic feature sequence associated with acoustic scenes (e.g. 'cooking') and acoustic events (e.g. 'cutting with a knife,' 'heating a skillet' or 'running water') called latent acoustic topic and event allocation (LATEA) model. The proposed model allows the analysis of a wide variety of sounds and the capture of abstract acoustic scenes by representing acoustic events and scenes as latent variables, and can also describe the acoustic similarity and variance between acoustic events by representing acoustic features as a mixture of Gaussian components. Experiments with real-life sounds indicated that the proposed model exhibited lower perplexity than conventional models; it improved the stability of acoustic scene estimation. The experimental results also suggested that the proposed model can better describe the acoustic similarity and variance between acoustic events than conventional models. © 2013 IEEE. Source

Shimauchi S.,NTT Media Intelligence Laboratories | Kobayashi K.,NTT Media Intelligence Laboratories | Fukui M.,NTT Advanced Technology Corporation | Kurihara S.,NTT Media Intelligence Laboratories | Ohmuro H.,NTT Media Intelligence Laboratories
NTT Technical Review

Automatically calibrating echo canceller software has been developed for voice over Internet protocol (VoIP) applications on smartphones. Because the audio properties of smartphones typically depend on the model, the speech quality of a VoIP application may sometimes degrade, especially during hands-free conversations. We extended the calibration ability of our software in order to handle the variations in smartphone audio properties. As a result, our software exhibited better performance than most conventional software. Source

Tsutsuguchi K.,NTT Media Intelligence Laboratories | Ando S.,NTT Media Intelligence Laboratories | Katayama A.,NTT Media Intelligence Laboratories | Tanaka H.,NTT Media Intelligence Laboratories | And 2 more authors.
NTT Technical Review

Mobile video watermarking technology is a digital watermarking technology that can detect invisible information embedded in external videos with both high speed and accuracy, simply by directing the camera in the mobile device towards the video. In this article, we give an overview of the technology and describe two example use case applications in existing broadcast TV services and a new opportunity using video synchronized augmented reality. Source

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