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Business—Technology Interface
Published in Klaus Diepold, Sebastian Moeritz, Understanding MPEG-4, 2012
Klaus Diepold, Sebastian Moeritz
The term “Channels” in these tables refers to an audio output channel. As you may know, stereo is a two-channel implementation, whereas mono is only one channel. The classification and breakdown into channels is pretty advantageous considering the fact that in MPEG-4 AAC, there are up to 48 full-frequency range audio channels. Pricing on a per-channel basis allows a much better differentiation between multi-channel (such as home theatre products) and simple mono or stereo products. The term “reset” basically means that the number of units sold or deployed in a previous quarter is disregarded, and every quarter is counted on its own in terms of units deployed, i.e., there is no roll-over or annual consideration.
What are architectural acoustics?
Published in Samuel L. Hurt, Building Systems in Interior Design, 2017
Systems are available for mono, stereo, and surround-sound. Mono means that there is one channel of sound with no directionality; if there are two speakers in the system, they both play the same thing. Stereo means that there are two channels (to mimic our hearing), which means that we can hear directionality—the whistle blew on the right side, for example. Surround-sound takes stereo to a whole new level, with five channels (front left, front middle, front right, rear left, and rear right), and we can get a complete sensation of sound in front of, next to, and behind us.
Tech Talk
Published in Stacy Zemon, Mobile DJ Handbook, 2013
In a sound reproducing system, stereo refers to the use of two separate signal processing channels driving two separate power amplifiers. These in turn power two separate speaker systems. However, most times in sound reinforcement, a stereo mixer is employed to drive a mono (single channel) system in order to have (submixes) separate instrument versus vocal mixes of the program.
Reconstructing room scales with a single sound for augmented reality displays
Published in Journal of Information Display, 2023
Benjamin S. Liang, Andrew S. Liang, Iran Roman, Tomer Weiss, Budmonde Duinkharjav, Juan Pablo Bello, Qi Sun
Figure 2 visualizes our computational pipeline that converts an IR from a stereo microphone recording to a 3D reconstruction of a reverberating physical environment. First, the IR is obtained by deconvolving a stereo recording of a stimulus signal played by a loudspeaker in the room. Next, we calculate the difference between the recordings of each stereo channel to yield a third signal to consider human perception of stereoscopic disparity, including difference in amplitude, distance of sound traveled, resonances, and anti-resonances. Then, we convert these three signals into a Mel-spectrogram (MS), a 2D time-frequency representation of reverberant energy, which we use as an image input to a CNN model which decodes the room's 3D dimensions. Simulated experiments demonstrate our method's accuracy and precision in predicting various three-dimensional spaces.
A novel strategy for effectively implementing a typical AVC scheme using finite element model updating
Published in Mechanics Based Design of Structures and Machines, 2019
Poonam Sood, Manu Sharma, Sukesha Sharma, Navin Kumar
To obtain the experimental modal data of the smart plate considered in this work, method based on DIC technique is employed (Cormick and Lord 2010). DIC technique is based on principle of stereo triangulation that uses two image sensors. In stereo triangulation the position of points is computed in 3 D using the projection of points on two or more images. Two high speed cameras (FASTCAM SA 5 from Photron®) with 8 GB memory are used as image sensors. High speed images are captured and stored in digital form. These images are later post processed using DIC algorithms to calculate the deformations or displacements. DIC algorithm used can calculate displacements with accuracy upto 0.01 pixel. Speckle pattern on the smart plate is generated using white aerosol paint and black marker. Position of 72 points corresponding to the nodes in the analytical FE model are marked on the plate to correlate with the measured response at these points (Fig. 3).
Development and field test of the articulated mobile robot T2 Snake-4 for plant disaster prevention
Published in Advanced Robotics, 2020
Motoyasu Tanaka, Kazuyuki Kon, Mizuki Nakajima, Nobutaka Matsumoto, Shinnosuke Fukumura, Kosuke Fukui, Hidemasa Sawabe, Masahiro Fujita, Kenjiro Tadakuma
On the sensor part, as shown in Figure 5, there are a visible light cameras (Pi camera module v2) to obtain the view of the operation by the gripper, a thermal camera (Lepton 3.0), and a CO2 sensor (MH-Z19) to detect abnormalities, and a stereo vision sensor (ZED mini) for visual simultaneous localization and mapping (Visual SLAM). The microphone is attached near the tip of the arm to detect abnormal noise. The data from the stereo vision sensor and microphone are processed at the Jetson TX2. A Raspberry Pi 3 Model B+ obtains the data of the visible light camera, thermal camera, and CO2 sensor, and sends them to the Jetson TX2 through an ethernet cable. The Jetson TX2 sends all obtained data to the operator station using the ROS network.