The project focuses on face detection and tracking to automate home appliances and reduce electricity consumption using MATLAB and IoT technology. It highlights the significant electricity generation and consumption in India and the need for energy conservation, addressing the problem of wastage due to negligence and inefficient practices. The methodology incorporates the Viola-Jones and Camshift algorithms for face detection and tracking, aiming to improve energy efficiency in various settings like homes and schools.

1. 8Th Semester Project
2018
FACE DETECTION AND TRACKING USING DIGITAL IMAGE
PROCESSING
Submitted to
Department of Electronics & Communication
Submitted By
Narayan Lal Menariya
Varun Bhatnagar

2. Content
• Electricity generation and Consumption in India
• Origin and definition of the Problem
• Need to save electricity?
• Method to reduce consumption and wastage.
• Project Work Plan
• Flow Chart
• Literature survey
• Methodology
• Implementation
• Result
• Minor Equipment
• Reference

3. SUMMARY
In this MATLAB based project we are extracting the frames from the video and
dividing each frame into two quadrant. After detecting the face in respective
quadrant we are setting the flag variable. This flag variable later can be used as a
switch for automatic controlling of the home appliances.

4. Electricity generation and Consumption in India
• India is the world's third largest producer and fourth largest
consumer of electricity (2016-2017).
• gross electricity generated was 1,236.39 TWh
• total electricity generation was 1,433.4 TWh
• The gross electricity consumption was 1,122 kWh per capita
• Current electricity generation depending on of fossil fuels(71% )
– coal (59.6%),
– Gas(9%),
– Oil(0.52%)
– Nuclear(1.9%)

5. Origin and definition of the Problem
• We do not waste electricity for any bad intentions
• but owing to our negligence and casual practices of electricity
use causes wastes
• Lack of awareness & importance of energy conservation
• Use of Inefficient equipment/appliances
• Mentality of “I can pay whatever I consume” thinking
• Negligent way of handling of energy utilities
• Fail to monitoring & auditing energy consumption bills
• present busy and stressful life

6. Need to save electricity?
• To reduce electricity bills.
• Electricity is not only fuel for our daily life but also vital for
countries economic growth (GDP growth).
• Reduce imports of fossil fuels (import rate of fossil fuel is 38 %
report by 2012) and increasing every year )
• Reduce impacts of fossil fuels on environment
– coal based power plant emits 1.1Kg(average) of CO for
producing 1 unit(kWh) of electricity.
– Oil, Gas & Coal are likely to last for only 20 years.
– we have Oil, Gas, Coal reserves of only 0.5% , 0.6% & 7%
respectively of the total world reserves.

7. How to reduce consumption and avoid wastage?
• Obviously we can ...
– use LED
– aware before using zero bulbs
– Use air conditioners, refrigerators, freezer at optimum temperature
– Etc...
• But what are the other steps ?
• Its the Era of Artificial Intelligence.
– Smart Home Automation attracted the interest of the research
community at the great manner
– But what if any person is impaired to send the message for controlling
the appliances.

8. Project Work Plan
• Save Electricity and provide Artificial Intelligence
– for Automatically Controlling of the home Appliances with MATLAB
image processing.
• Supposed to have any room
– Room is divided into specific quadrants
– corresponding quadrants having some appliances
– supposed to switch on and off according to the presence of person in
corresponding quadrant
• Once the image and its quadrant are detected
– corresponding appliances are controlled with the help of
microprocessor interrupts and internet of things (IoT).

9. PROCEDURE OF FACE DETECTION
• Step 1: Read frame from CCTV camera
• Step 2: Matrix dimension into four Quadrants as shown in
figure
• Step 3: Check for any face detection of person
• Step 4: Check for the respective quadrant where the face is
detected
• Step 5: Actuate the respective appliances of that quadrant
• Step 6: Repeat from Step 1

10. Literature Survey

11. Literature survey
Viola-Jones algorithm: Two features are selected for the task of face
detection:
1. first feature: the region of the eyes is often darker than the region
of the nose and cheeks
2. second feature: the eyes are darker than the bridge of the nose

13. Viola-Jones algorithm
3. Classifier can be constructed which reject many of the
negative sub windows while detecting almost all positive
instances.
4. The final detector is scanned across the image at multiple
scales and locations
5. The detector is also scanned across location, by shifting the
window some number of pixels
6. It is useful to post process the detected sub-windows in
order to combine overlapping detections into a single
detection.

14. FACE TRACKING

15. Literature Survey
CAMShift Algorithm:
1. Set the region of interest (ROI) of the probability distribution
image to the entire image.
2. Select an initial location of the Mean Shift search window. The
selected location is the target distribution to be tracked.
3. Calculate a color probability distribution of the region centred at
the Mean Shift search window.
4. Iterate Mean Shift algorithm to find the centroid of the probability
image. Store the zeroth moment (distribution area) and centroid
location.
5. For the following frame, center the search window at the mean
location found in Step 4 and set the window size to a function of
the zeroth moment. Go to Step 3.

16. Methodology

17. Implementation
• a simple face tracking system can be design by dividing the
tracking problem into three separate problems:
– Detect a face to track
– Identify facial features to track
– Track the face
Step-1: Detect a Face To Track
• vision.CascadeObjectDetector used to detect the location of a
face in a video frame
• The cascade object detector uses the Viola-Jones detection
algorithm and a trained classification model for detection

18. Step-2: Identify Facial Features To Track
• shape, texture, or color can be used to track the face.
• In this example, we use skin tone as the feature to track.
– Extract the frame from video
– Convert each frame into hue using rgb2hsv() function
– Display the Hue Channel data and draw the bounding box around the
face.
Step 3: Track the Face
• After selecting skin tone as a tracking feature histogram based
tracker can be used to track the face
• Histogram based tracker uses the CamShift algorithm
Implementation

19. Implementation
• video player object is created for displaying the video
• Track the face over successive video frames until the video is
finished.

20. Results
Class Room

21. Result
Quadrants Division of class room

22. Result
Face Detection in Two Quadrant
flag1 = 0; flag2=1;

23. Result
If(flag1 == 1)
switch on the appliances of quadrant1
Else
switch off the appliances of quadrant1
If(flag2 == 1)
switch on the appliances of quadrant2
Else
switch off the appliances of quadrant2

24. Minor Equipment
• CCTV Camera
• MATLAB Software
• Raspberry Pi Board
• NRF24L01 with antenna

25. Proposed outcome
• Save wastage of Electricity
• IoT Based project
• No need of Manual controlling of home appliance
• Low cost
• Applicable at
– Home
– Hospital
– School
– Etc
• No requirement of larger area for project installation
• Less maintenance is required

26. Reference
• Electricity Sector in India – Wikipedia
(https://en.wikipedia.org/wiki/Electricity_sector_in_India )
• Image source – Google
• MATLAB Help menu
• Youtube – Matlab Image Processing
• MATALB Reference note by Cranes Varsity

27. Thanking you...