GUJARAT TECHNOLOGICAL UNIVERSITY
938070250406Chandkheda, Ahmedabad Affiliated
Silver Oak College Of Engineering And Technology
A Report On-
Recognization Of Hand Movement Using Nueral Network
Under Subject Of DESIGN ENGINEERING
B. E. II, Semester – III
(Computer Engineering Branch)
Sr.Name of studentEnrolment No.
Academic year (2018-2019)
We have finished our project report entitled recognization of hand movement using nueral network and submitted to our respected guide. We are in 3rd semester and we have tried to give our best. We have done our work honestly and in a good way.
First candidate name: Shabnam Sandhi
Branch: Computer engineering
Second candidate name: Khushbu Patel
Branch: Computer engineering
Third candidate name: Yesha Patel
Branch: Computer engineering
Fourth candidate name: Titiksha Deviaya
Branch: Computer engineering
Submitted to silver oak college of engineering and technology, ahmedabad affiliated to: Gujarat technological university .
We would like to extend our heartly thanks with a deep sense of gratitude and respect to all those who has provide us the immense help and guideance during our project.
We would like to express our sincere thanks to our internal guide Kyati Raval for providing the vision about the system and for giving us an opportunity to undertake such a great chanllenging and innovative work. We are gratefull for guidance, encouragement, understanding and insightfull supportgiven in the development process.
We would like to extend my gratitude to head of Computer Engineering Department, Silver Oak college of Engineering and Technology, Ahmedabad, for his continuous encouragement and motivation.
Last but not the least we would like to mention here that we are greatly indebted to each and everybody who has been associated with our project at any stage but whose name does not find a place in this acknowledgement.
Yours Sincerely ,
Titiksha Deviaya(170770107 038)
Hand gesture regonisation system is used for interfacing between computer and human using hand gesture. We wish to make a windows-based application for live motion gesture recognisation using webcam input in C++. This projecy is a combination of live motion detection and gesture identification. This application uses the webcam to detect gesture made by the user and perform basic operation accordingly. The user has to perform a particular gesture. The webcam captures this and identifies the gesture, recognizes it and perform the action corresponding to it. This application can be made to run in the background while the user runs other programs and applications. This is very useful for a hands-free approach. While it may to be great use for browsing the webor writing a text document, it is useful in media player files. A simple gesture could pause or play the movie or increase the volume even while sitting afar from the computer screen. One could easily scroll through an ebook or a presentation even while having lunch.
Various features of the code of the projects are:
Can detect any kind of gesture which is provided in the database. Eliminates the background so can be operated in a place where there is no much movement in the background. The movement of the haed while performing the gesture are eliminated.
a)Observation through AEIOU methods and others
Activities are directly or indirectly related to stakeholders.
Activities are work done by stakeholders by stakeholders on a particular workplace.
It is used to detect any kind of gesture and makes people’s life easy.
Communication is done between patient-computer.
2. Environment :-
Environments include the entire arena where activities take place.
What is the character and function of the space overall, of each individual;s spaces, and of shared spaces?
It is the surrounding of particular workspace related to selected domain.
Example :- Hospitals, laboratories, houses.
3. Interaction :-
Interactions are between a person and someone or something else; they are the building blocks of activities.
What is the nature of routine and special interactions between people;
between people and objects in their environment, and across distances?
4. Objects :-
Objects are building blocks of the environment, key elements sometimes put to complex or unintended uses (thus changing their function, meaning and context).
What are the objects and devices people have in their environments and how do they relate to their activities?
Example:- Hand gesture, virtual objects, recognization, tracking.
5. Users :-
Users are the people whose behaviors, preferences, and needs are being observed.
Who is there?
What are their roles and relationships?
What are their values and prejudices?
Example:- Patient, paralytic person.
b) Role playing:-
d)mind mapping:- “A mind map is ?a visual representation of ?hierarchical information that includes a central idea surrounded by?connected branches of associated topics”
e) empathy mapping canvas:-
– Users are the people whose behaviours, preferences, and needs are being observed.
-Who is there? What are their roles and relationships? What are their values and prejudices?
Content which is included in our project:-
People who suffer from paralysis
Even people who cant speak can use it to easily communicate.
-Which are not use the system directly..that means indirect users
Contents which is included our project:
-Someone (User) is involved…
-What actually is going on?
-Why it is going on?
-How it is going on?
-What is involved?
Contents which is included in our project:
1.can detect any kind of gesture which is provided in the database.
2.eliminates the background so can be operated in a place where there is no much movement in the background.
3.the movements of the head while performing the gesture are eliminated.
4. Story boarding :-
Simple,fast and easy to implement
There is no training required for this system.
Makes life easy.
Recognization is static and dynamic gesture
Attaching sensor with gloves mechanism
Vision based analysis.
Analysis of drawing gesture.
irrelevent objects might overlapped with hand.
Finger should in basic colour.
Ambient light effects the colours detection threshold.
This includes people who are directly affected by the product, i.e. the real customer:-
Paralytic persons:- as their body movements are restricted, they cant communicate very effectively so this project is for them
Stroke patients:-they are told not to mave much so mit usefull for them
Dumb:- as people cant spesk they can effectively communicate through this.
The activites are
Processing to focus on the gesture.
A classification for the unknown gesture feature produce to the neural network.
Information processing occurs at many neurons.
Signals are passed between neurons over connection link
Each connection link has associated weight which is a typical nearl set is s typical neural set the single transmitted.
The developer has to provide system that correctly recognises this gesture.
The developers not onl;y has to ensure that gestures are quickly and correctly recognized but also has to provide a guiode that allows a rapid and easy learnings.
Product Development Canvas
Purpose of this project is to make the life of paralytic people and people who needs help in speaking easy.
Results are quick and accurate
Comfortable for customers easy to maintain
The target of this system is to accurate and good results and at the same time results take less time.
This charecteristics is used to identify the object .
It is used to recognized the hand movement.
It makes communication easy.
Bad UX design
8.Reject redesign and retain
Improve UX design
More training data provided
The importance of gesture recognition lies in building efficient human–machine interaction. Its applications range from sign language recognition through medical rehabilitation to virtual reality. Constructing an efficient hand gesture recognition system is an important aspect for easily interaction between human and machine. In this work we provided a comparative study on various gesture recognition systems with emphasis on detection, tracking and recognition phases which are essential for gesture detection and extraction. Over the last decade numerous methods for gesture taxonomies and representations have been evaluated for the core technologies proposed in the gesture recognition systems. However the evaluations are not dependent on the standard methods in some organized format but have been done on the basis of more usage in the gesture recognition systems
Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current focuses in the field include emotion recognition from face and hand gesture recognition. Users can use simple gestures to control or interact with devices without physically touching them. Many approaches have been made using cameras and computer vision algorithms to interpret sign language. However, the identification and recognition of posture, gait, proxemics, and human behaviors is also the subject of gesture recognition techniques.1 Gesture recognition can be seen as a way for computers to begin to understand human body language, thus building a richer bridge between machines and humans than primitive text user interfaces or even GUIs (graphical user interfaces), which still limit the majority of input to keyboard and mouse.
Gesture recognition enables humans to communicate with the machine (HMI) and interact naturally without any mechanical devices. Using the concept of gesture recognition, it is possible to point a finger at the computer screen so that the cursor will move accordingly. This could make conventional input devices such as mouse, keyboards and even touch-screens redundant