FYP Reflection 1
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For this reflection it is about how I starts my project. A little explanation of the problems and address some improvement occurs from my findings. Then, I end this reflection with the possible hypothesis device estimation to solve the problem.
Date: 18/11/21 (Week 5)
Supervisor Name: Assoc. Prof. Ts. Dr. Nasrul Humaimi Bin Mahmood
Proposed Topic: Assistive Spectacle Camera Recognition of General Object for Visual Impairment Person
I attended a briefing session that was held by Dr. Mohd Amri bin Md Yunus through Webex and we are discussing the Final Year Project (FYP) regarding the information, the guideline and generally about what we have to do. Next, I and another student have our first meeting with my supervisor, Assoc. Prof. Ts. Dr. Nasrul Humaimi Bin Mahmood to discuss about finding topics for our the FYP project. But before that, we had a little ice breaking with my team members who were under the same supervision. After that, my supervisor asked us whether we already had a topic or not because he had a few suggestion topics related to the biomedical devices project. As for me, I does not have a proper idea as my idea is just roughly proposed. He them help me and suggest device that helps visual impairment such an assistive spectacle camera recognition of general object for visual impairment person. He advice us to search some project that is high demand in market currently and help disable people as it could attracts more attention. After getting a clear vision of my project title, I then prepared at least 3 keyword (smart glasses, object identification, camera recognition) to find my reading materials that related to my research topic.
This project is to help human in needs especially visual impairment person who needs guidance to recognize thing or navigate. I will explain the addressed problems, things to improve and goals of my project. From the reading materials that I have found, the main problem in my research is to know the effectiveness and the performance of the device. In that case, I decided to find the best method, to make this project to be uncomplicated and easy to access thus, this could make it a user friendly device. As for the goal of the project, it is to study the method of object detection that is resistant to lighting conditions and the angle. It could help the human in needs specifically for visual impairment person.
Basically my project device will detect an object. Then it will help visual impairment by voicing it out what the object is. Figure below shows the flow diagram of the expected prototype design will be.
Figure 1: Flow diagram of the prototype design.
According to the diagram, the input is from the capture of real time video by the camera. Then it will process by the object detection algorithm and deep neural network processing unit until the object detected and identified. The last step is the output, which it will voice out through the speaker according to the text speech processing unit.
FYP Reflection 2
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For this reflection it is about how my project progress and process. A little review on the literature related to the problem addressed. Then, state the scope of working process and the method flow of work. I end this reflection by mention on what knowledge/skills required to do the project and the hardware/software requirement to finish the project.
Date: 16/12/21 (Week 9)
Supervisor Name: Assoc. Prof. Ts. Dr. Nasrul Humaimi Bin Mahmood
Proposed Topic: Assistive Spectacle Camera Recognition of General Object for Visual Impairment Person
Object Detection, Tracking and Recognition for Multiple Smart Cameras
For cameras that have no overlapping fields of views, object association can be achieved by learning the relationship between patterns of entry and exit in various camera views. For cameras with overlapping fields of views, an important issue that arises is fusion of object location estimates.
Wearable Smart Glass: Features, Applications, Current Progress and Challenges
As the smart glass involves many components and instruments, electronic and computer network interfacing devices, the wearer would feel difficulty. It seems that wearable smart glass has good scope for the development as well as the contributions in many application areas.
Low Cost Ultrasonic Smart Glasses for Blind
Traditional navigation device mostly blind cane, blind by tapping the ground or walking around the object to determine the direction, the structure is simple, single function, easy to use, but ordinary cane cannot be proven accurate, such a serious impact on the safety of blind travelers.
Smart Glasses using Deep Learning and Stereo Camera
In the past, the blind people used ordinary cane or trained guide dog. Conventional assistive canes have a low detection rate for obstacles and limited detection area. In the case of guide dog, there are places that cannot be accessed, and there is a high cost for managing and training guide dog.
Deep learning algorithm cannot be performed on low level MCU of smart glasses since this algorithm compute with a lot of data. To perform fast computation, image data is transmitted to the server using wireless communication.
Real Time Multi Object Detection for Blind Using Single Shot Multibox Detector
There are three object detection methods in deep learning based object detection—RCNN, YOLO and SSD. SSD is much faster compared to YOLO and also as accurate as slower techniques that perform region proposals are pooling. So it is suitable for resource constrained devices regarding size, memory and graphical processing speed.
A Convolutional Neural Network based Live Object Recognition System as Blind Aid
The project will accurately detect the surrounding objects using YOLO Algorithm and convert into voice feedback using gTTs. This project made with the help of Deep Leaning and Raspberry pi will greatly help visually impaired individuals to the great extent by acting as a tool connecting them to the world and surpassing their disability of vision.
- Conceptual design/prototype
- Hardware and software development
- Assemble and programming
- Test device and fine tune
- Evolution of the report
- Object
- Real time video
- Microprocessor (Raspberry pi)
- Digital image processing system
- Object detection algorithm
- Deep neural network processing unit
- Object identified images
- Text speech processing unit (gTTs)
- Voice feedback
- Programming skills and understanding
- Testing the programming coding
- Data collection and analyze
- Assemble devices
- Troubleshoot error
- Camera
- Raspberry pi
- Earphones
- Python
- Yolo v3/Single shot detector
- Voice (google text to speech)