Client Profile: Digi International, Inc

Contact: Elizabeth Presson
elizabeth.presson@digi.com

Featured Product: The XBee product family (www.digi.com/xbee) is a series of modular products that make adding wireless technology easy and cost-effective. Whether you need a ZigBee module or a fast multipoint solution, 2.4 GHz or long-range 900 MHz—there’s an XBee to meet your specific requirements.

XBee Cloud Kit

Digi International XBee Cloud Kit

Product information: Digi now offers the XBee Wi-Fi Cloud Kit (www.digi.com/xbeewificloudkit) for those who want to try the XBee Wi-Fi (XB2B-WFUT-001) with seamless cloud connectivity. The Cloud Kit brings the Internet of Things (IoT) to the popular XBee platform. Built around Digi’s new XBee Wi-Fi
module, which fully integrates into the Device Cloud by Etherios, the kit is a simple way for anyone with an interest in M2M and the IoT to build a hardware prototype and integrate it into an Internet-based application. This kit is suitable for electronics engineers, software designers, educators, and innovators.

Exclusive Offer: The XBee Wi-Fi Cloud Kit includes an XBee Wi-Fi module; a development board with a variety of sensors and actuators; loose electronic prototyping parts to make circuits of your own; a free subscription to Device Cloud; fully customizable widgets to monitor and control connected devices; an open-source application that enables two-way communication and control with the development board over the Internet; and cables, accessories, and everything needed to connect to the web. The Cloud Kit costs $149.

Natural Human-Computer Interaction

Recent innovations in both hardware and software have brought on a new wave of interaction techniques that depart from mice and keyboards. The widespread adoption of smartphones and tablets with capacitive touchscreens shows people’s preference to directly manipulate virtual objects with their hands.

Going beyond touch-only interaction, the Microsoft Kinect sensor enables users to play

This shows the hand tracking result from Kinect data. The red regions are our tracking results and the green lines are the skeleton tracking results from the Kinect SDK (based on data from the ChAirGest corpus: https://project.eia-fr.ch/chairgest/Pages/Overview.aspx).

This shows the hand tracking result from Kinect data. The red regions are our tracking results and the green lines are the skeleton tracking results from the Kinect SDK (based on data from the ChAirGest corpus: https://project.eia-fr.ch/chairgest/Pages/Overview.aspx).

games with their entire body. More recently, Leap Motion’s new compact sensor, consisting of two cameras and three infrared LEDs, has opened up the possibility of accurate fingertip tracking. With Project Glass, Google is pioneering new technology in the wearable human-computer interface. Other new additions to wearable technology include Samsung’s Galaxy Gear Smartwatch and Apple’s rumored iWatch.

A natural interface reduces the learning curve, or the amount of time and energy a person requires to complete a particular task. Instead of a user learning to communicate with a machine through a programming language, the machine is now learning to understand the user.

Hardware advancements have led to our clunky computer boxes becoming miniaturized, stylish sci-fi-like phones and watches. Along with these shrinking computers come ever-smaller sensors that enable a once keyboard-constrained computer to listen, see, and feel. These developments pave the way to natural human-computer interfaces.
If sensors are like eyes and ears, software would be analogous to our brains.

Understanding human speech and gestures in real time is a challenging task for natural human-computer interaction. At a higher level, both speech and gesture recognition require similar processing pipelines that include data streaming from sensors, feature extraction, and pattern recognition of a time series of feature vectors. One of the main differences between the two is feature representation because speech involves audio data while gestures involve video data.

For gesture recognition, the first main step is locating the user’s hand. Popular libraries for doing this include Microsoft’s Kinect SDK or PrimeSense’s NITE library. However, these libraries only give the coordinates of the hands as points, so the actual hand shapes cannot be evaluated.

Fingertip tracking using a Kinect sensor. The green dots are the tracked fingertips.

Our team at the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory has developed methods that use a combination of skin-color and motion detection to compute a probability map of gesture salience location. The gesture salience computation takes into consideration the amount of movement and the closeness of movement to the observer (i.e., the sensor).

We can use the probability map to find the most likely area of the gesturing hands. For each time frame, after extracting the depth data for the entire hand, we compute a histogram of oriented gradients to represent the hand shape as a more compact feature descriptor. The final feature vector for a time frame includes 3-D position, velocity, and hand acceleration as well as the hand shape descriptor. We also apply principal component analysis to reduce the feature vector’s final dimension.

A 3-D model of pointing gestures using a Kinect sensor. The top left video shows background subtraction, arm segmentation, and fingertip tracking. The top right video shows the raw depth-mapped data. The bottom left video shows the 3D model with the white plane as the tabletop, the green line as the arm, and the small red dot as the fingertip.

The next step in the gesture-recognition pipeline is to classify the feature vector sequence into different gestures. Many machine-learning methods have been used to solve this problem. A popular one is called the hidden Markov model (HMM), which is commonly used to model sequence data. It was earlier used in speech recognition with great success.

There are two steps in gesture classification. First, we need to obtain training data to learn the models for different gestures. Then, during recognition, we find the most likely model that can produce the given observed feature vectors. New developments in the area involve some variations in the HMM, such as using hierarchical HMM for real-time inference or using discriminative training to increase the recognition accuracy.

Ying Yin

Ying Yin is a PhD candidate and a Research Assistant at the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Laboratory. Originally from Suzhou, China, Ying received her BASc in Computer Engineering from the University of British Columbia in Vancouver, Canada, in 2008 and an MS in Computer Science from MIT in 2010. Her research focuses on applying machine learning and computer vision methods to multimodal human-computer interaction. Ying is also interested in web and mobile application development. She has won awards in web and mobile programming competitions at MIT.

Currently, the newest development in speech recognition at the industry scale is a method called deep learning. Earlier machine-learning methods require careful selection of feature vectors. The goal of deep learning is automatic discovery of powerful features from raw input data. So far, it has shown promising results in speech recognition. It can possibly be applied to gesture recognition to see whether it can further improve accuracy.

As component form factors shrink, sensor resolutions grow, and recognition algorithms become more accurate, natural human-computer interaction will become more and more ubiquitous in our everyday life.

Dual-Channel Waveform Generators

B&K Precision 4053 Waveform Generator

B&K Precision 4053 Waveform Generator

The 4050 Series is a new line of four dual-channel function/arbitrary waveform generators. The instruments can generate 5-to-50-MHz waveforms for applications requiring stable and precise sine, square, triangle, and pulse waveforms with modulation and arbitrary waveform capabilities.

All models provide a main output voltage that can be vary from 0 to 10 VPP into 50 Ω and a secondary output that can vary from 0 to 3 VPP into 50 Ω. The generators feature a 3.5” color LCD, a rotary control knob, and a numeric keypad with dedicated waveform keys and output buttons.

The 4050 Series provides users with 48 built-in arbitrary waveforms. Using the included waveform editing software via the standard USB interface on the rear, users can create and load up to 10 custom 16-kpt waveforms. For general-purpose interface bus (GPIB) connectivity, an optional USB-to-GPIB adapter is available.

The generators offer a variety of modulation schemes for modulated signal applications including amplitude and frequency modulation (AM/FM), double sideband amplitude modulation (DSB-AM), amplitude and frequency shift keying (ASK/FSK), phase modulation (PM), and pulse-width modulation (PWM). Additional standard features include a linear and logarithmic sweep function, a built-in counter, sync output, a trigger I/O terminal, and a USB host port on the front panel to save and recall instrument settings and waveforms. A standard external 10-MHz reference clock input is provided to synchronize the instrument to another generator.

The 4052 (5-MHz) costs $499, the 4053 (10 MHz) costs $599, the 4054 (25 MHz) costs $850, and the 4055 (50 MHz) costs $1,050. Note: B&K Precision is offering 10% off MSRP through November 30, 2013. See website for details.

B&K Precision Corp.
www.bkprecision.com

Client Profile: Netburner, Inc

NetBurner, Inc.
5405 Morehouse Drive
San Diego, CA 92121

www.netburner.com

Contact: sales@netburner.com

Embedded Products/Services: The NetBurner solution provides hardware, software, and tools to network enable new and existing products. All components are integrated and fully functional, so you can immediately begin working on your application.

Product Categories:

  • Serial to Ethernet: Modules can be used out of the box with no programming, or you can use a development kit to create your own custom applications. Hardware ranges from a single chip to small modules with many features.
  • Core Modules: Typically used as the core processing module in a design, core modules include the processor, flash, RAM and on-board network capability. The processor pins are brought out to connectors and include functions such as SPI, I2C, address/data bus, ADC, DAC, UARTs, digital I/O, PWM, and CAN.
  • Development Kits: Development kits can be used to customize any of NetBurner’s Serial-to-Ethernet or Core Modules. Kits include the Eclipse IDE, a C/C++ compiler/linker, a debugger, a RTOS, a TCP/IP stack, and board support packages.

Product Information: The MOD54415 and the NANO54415 modules provide 250-MHz processor, up to 32 MB flash, 64 MB DDR, ADC, DAC, eight UARTs, four I2C, three SPI, 1-wire, microSD flash socket, five PWM, and up to 44 digital I/O.

Exclusive Offer: Receive 15% off on select development kits. Promo code: CIRCUITCELLAR


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Low-Cost, High-Performance 32-bit Microcontrollers

The PIC32MX3/4 32-bit microcontrollers are available in 64/16-, 256/64-, and 512/128-KB flash/RAM configurations. The microcontrollers are coupled with Microchip Technology’s software and tools for designs in connectivity, graphics, digital audio, and general-purpose embedded control.

The microcontrollers offer high RAM memory options and high peripheral integration at a low cost. They feature 28 10-bit ADCs, five UARTS, 105-DMIPS performance, serial peripherals, a graphic display, capacitive touch, connectivity, and digital audio support.
The PIC32MX3/4 microcontrollers are supported with general software development tools, including Microchip Technology’s MPLAB X integrated development environment (IDE) and the MPLAB XC32 C/C++ compiler.

Application-specific tools include the Microchip Graphics Display Designer X and the Microchip Graphics Library, which provide a visual design tool that enables quick and easy creation of graphical user interface (GUI) screens for applications. The microcontrollers are also supported with a set of Microchip’s protocol stacks including TCP/IP, USB Device and Host, Bluetooth, and Wi-Fi. For digital audio applications, Microchip provides software for tasks such as sample rate conversion (SRC), audio codecs—including MP3 and Advanced Audio Coding (AAC), and software to connect smartphones and other personal electronic devices.

The PIC32MX3/4 family is supported by Microchip’s PIC32 USB Starter Kit III, which costs $59.99 and the PIC32MX450 100-pin USB plug-in module, which costs $25 for the modular Explorer 16 development system. Pricing for the PIC32MX3/4 microcontrollers starts at $2.50 each in 10,000-unit quantities.

Microchip Technology, Inc.
www.microchip.com