Multimodal Signal Processing: Methods and Techniques to Build Multimodal Interactive Systems
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Microsoft Kinect, Google's Project Tango and Lytro's light field camera are all examples of 3D depth sensing reaching the consumer market. As this technology becomes more widestream, new signal processing techniques are needed to exploit this data. Recent ...
According to the U.S. Bureau of Labor Statistics, during 2013 employed Americans "worked an average of 7.6 hours on the days they worked," and "83% did some or all of their work at their workplace" [1]. Understanding processes in the workplace has been the ...
Functional brain networks reconfigure spontaneously during rest. Such network dynamics can be studied by dynamic functional connectivity (dynFC); i.e., sliding-window correlations between regional brain activity. Key parameters-such as window length and cu ...
The technological evolution of optical sensors over the last few decades has provided remote sensing analysts with rich spatial, spectral, and temporal information. In particular, the increase in spectral resolution of hyperspectral images (HSIs) and infra ...
Institute of Electrical and Electronics Engineers2014
In real-word applications, signal processing is often used to measure and control a physical field by means of sensors and sources, respectively. An aspect that has been often neglected is the optimization of the sources' locations. In this work, we discus ...
This paper investigates the reduction of dynamic power for streaming applications yielded by asynchronous dataflow designs by using clock gating techniques. Streaming applications constitute a very broad class of computing algorithms in areas such as signa ...
High-resolution Doppler is a popular tool for evaluating cardiovascular physiology in mutant mice, though its 1-D nature and spectral broadening processes complicate interpretation of the measurement. Hence, it is crucial for pre-clinical researchers to kn ...
A Python package for room acoustics. This package would allow us to simulate sound propagation in a closed room allowing us to predict a situation, compare it with experimental results or apply calculations for various signal processing applications. ...
Inherently error-resilient applications in areas such as signal processing, machine learning and data analytics provide opportunities for relaxing reliability requirements, and thereby reducing the overheads incurred by conventional error correction scheme ...
Choosing a distance preserving measure or metric is fun- damental to many signal processing algorithms, such as k- means, nearest neighbor searches, hashing, and compressive sensing. In virtually all these applications, the efficiency of the signal process ...