S15: Hand Gesture Recognition using IR Sensors

Abstract

The aim of the project is to develop hand gesture recognition system using grid of IR proximity sensors. Various hand gestures like swipe, pan etc. can be recognized. These gestures can be used to control different devices or can be used in various applications. The system will recognize different hand gestures based on the values received from IR proximity sensors.

Objectives & Introduction

We use various hand gestures in our day-to-day life to communicate while trying to explain someone something, direct them somewhere etc. It would be so cool if we could communicate with various applications running on the computers or different devices around us understand the hand gestures and give the expected output. In order to achieve this, we are using a 3-by-3 grid of analog IR proximity sensors and connecting these sensors via multiplexers to the ADC pins on SJOne Board. As a hand is moved in front of the sensors, the sensor values would in a particular pattern enabling us to detect the gesture and instruct the application to perform the corresponding action.

Team Members & Responsibilities

• Harita Parekh
  • Implementing algorithm for gesture recognition
  • Implementation of sensor data filters
• Shruti Rao
  • Implementing algorithm for gesture recognition
  • Interfacing of sensors, multiplexers and controller
• Sushant Potdar
  • Implementation of final sensor grid
  • Development of the application module

Schedule

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Week#	Start Date	End Date	Task	Status	Actual Completion Date
1	3/22/2015	3/28/2015	Research on the sensors, order sensors and multiplexers	Completed	3/28/2015
2	3/29/2015	4/4/2015	Read the data sheet for sensors and understand its working. Test multiplexers	Completed	4/4/2015
3	4/5/2015	4/11/2015	Interfacing of sensors, multiplexers and controller	Completed	4/15/2015
4	4/12/2015	4/18/2015	Implementation of sensor data filters Implement algorithm to recognize left-to-right movement	Ongoing
5	4/19/2015	4/25/2015	Implementation of final sensor grid Implement algorithm to recognize up-to-down movement Implement algorithm to recognize right-to-left movement	Scheduled
6	4/26/2015	5/2/2015	Implement algorithm to recognize pan movement Implement algorithm to recognize down-to-up movement Develop the application module	Scheduled
7	5/3/2015	5/9/2015	Testing and bug fixes	Scheduled
8	5/10/2015	5/16/2015	Testing and final touches	Scheduled
9	5/25/2015	5/25/2015	Final demo	Scheduled

Parts List & Cost

SR#	Component Name	Quantity	Price per component	Total Price
1	Sharp Distance Measuring Sensor Unit (GP2Y0A21YK0F)	9	$14.95	$134.55
2	STMicroelectronics Dual 4-Channel Analog Multiplexer/Demultiplexer (M74HC4052)	3	$	$
3	SJ-One Board	1	$80	$80

Design & Implementation

Hardware Design

The image shows the setup of the project.

System Block Diagram: The system consists of 9 IR proximity sensors, which are arranged in 3x3 grid. The output of the sensors is given to the Analog-to-Digital convertor on the SJOne Board to get the digital equivalent of the voltage given by the sensors. Since there are only 3 ADC channels exposed on the pins on the board, we cannot connect all the sensors directly to the board. For these we have used three multiplexers, which has 3 sensors each connected to its input. The output of the multiplexers is connected to ADC. SJOne board is connected to the laptop via UART-to-USB connection.
Proximity Sensor: This sensor by Sharp measures the distance from an obstacle by bouncing IR rays off the obstacle. This sensor can measure distances from 10 to 80 cms. The sensor returns an analog voltage corresponding to the distance from the obstacle. Depending on which sensor returns valid values, validations could be made and hand movement can be determined. There is no external circuitry required for this sensor. The operating voltage recommended for this sensor is 4.5V to 5.5V.
Multiplexer: The chip used in the project is M74HC4052 from STMicroelectronics. This is a dual 4-channel multiplexer/demultiplexer. Due to shortage of ADC pins to interface with the sensors, use of multiplexer is required. The multiplexer takes input from three sensors and enables only one of them at the output. The program logic decides which sensor’s output should be enabled at the multiplexer’s output. A and B control signals select one of the channel out of the four. The operating voltage for the multiplexer is 2 to 6V.
UART-to-USB convertor: To communicate to SJONE board over UART there is a need an USB to serial convertor and a MAX232 circuit to convert the voltage levels to TTL, which the SJONE board understands. Instead it’s better to use a UART-to-USB convertor to avoid the multiple conversions. This is done using CP2102 IC, which is similar to a FTDI chip.

Hardware Interface

Pin connections for IR Sensor to Multiplexer:

Pin connections on SJOne board:

Connections between SJOne board and UART-to-USB Convertor:

Software Design

Filter Algorithm

State Machine Diagram:

Application Development QT Software QT is a cross-platform application framework that is widely used in developing application software that can be run on various software and hardware platforms with little or no change in the underlying codebase while having the speed and the power of native application. [1] It is mainly used to make GUI based applications but there can be applications such as consoles or command-line applications developed in QT. QT is preferred by many application programmers as it helps in developing GUI applications in C++ as it uses the standard C++ libraries for backend. Platforms supported by Qt are: Android Embedded Linux Integrity iOS OSX QNX VxWorks Waylands Windows Windows CE Windows RT X11 QT applications are highly portable from one platform to other as QT first runs a Qmake function before compiling the source code. It is very similar to ‘cmake’ which is used for cross platform compilation of any source code. The qmake auto generates a makefile depending on the operating system and the compiler used for the project. So if a project is to be ported from windows to linux based system then the qmake auto generated a new makefile with arguments and parameters that the g++ compiler expects.

Implementation

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Testing & Technical Challenges

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My Issue #1

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Conclusion

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Project Video

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Project Source Code

• Sourceforge Source Code Link

References

Acknowledgement

All the components where procurred from Amazon, Adafruit and digikey. We are thankful to Preet for his continuous guidance during the project.

References Used

IR Sensor Data Sheet
LPC_USER_MANUAL
Multiplexer Data Sheet
QT Software