Robotics 1
Image Subtraction
Quiz
Question 2: Suppose I have a pixel with [R,G,B] values of [255,255,255].  What color is that pixel?
Question 3:  Look at the color diagram in the Color Subtraction video at timestamp 2:00.  What [R,G,B] values would you expect a Magenta object to have?
Question 4:  Suppose that I have a Magenta pixel and I subtract a Cyan pixel.  Then, I limit the output so that any negative value becomes 0 and any value greater than 255 becaomes 255.  What color will the resulting pixel be?
Question 5:  Let's check to make sure you understand the 'center of mass' approach to finding an object location.  Shown here is a grayscale (8-bit depth) image matrix.  What is the 'column location' (left-to-right location) of the object?  Don't enter any units, just enter a number.  Assume that the left-most column is column 1 (not column 0), and round your answer to three places after the decimal.
Question 6:  For question 5, if you were going to put units on your answer, what units would you use?
Question 7:  For question 5, what is the 'row location' (up-and-down location) of the object?  Don't enter any units, just enter a number.  Assume that the top-most row is row 1 (not row 0), and round your answer to three places after the decimal.
Question 8:  Background subtraction only works when...
Question 9: Which of the following will make background subtraction fail?
Question 10: Which of these will make background subtraction fail?
Question 11:  Suppose I have a slow-moving object motion detection operation and a fast-moving object motion detection operation.  For which one will I choose a smaller value of 'delta t'?
Questions 13:  Which of the following is a reason you might want to select a LARGER value of 'delta t' in a particular situation?
Question 15: Suppose that your hand is 3 inches wide and you are going to move your hand across the screen at 1 foot per second.  Also, suppose that your camera resolution is 640x480.  What value should you set as 'delta t' to most effectively capture this motion?  Give your answer in units of seconds, but enter only a number in the box.  Round your answer to two places after the decimal.
Question 1: We can perform mathematical operations on images, such as addition, subtraction, multiplication, and division.
True
False
Black
Cyan
Yellow
White
[255,255,255]
Black
White
Green
Meters
Feet
Lumens
Pixels
The color of the object to be found is known
The color of the object to be found is the same color as the background
The object to be found is brighter than the background
The object to be found enters or leaves the view
[0,255,255]
[255,0,255]
[255,255,0]
Red
The color of the object to be found is not known
The object to be found is darker than the background
The camera is moving
The size of the object to be found is not known
The object to be found is moving
The object to be found is black
The object to be found is white
The color of the object to be found is the same color as the background
Question 12:  Which of the following is a reason you might want to select a SMALLER value of 'delta t' in a particular situation?
A smaller value of delta t will give a higher sampling rate, allowing for more effective motion tracking.
Questions 14:  Once we have done the motion detection step, what additional step do we need to do to figure out the location of the motion?
The slow-moving object
The fast-moving object
Neither; they should have the same value of delta t
A smaller value of delta t will act as a low-pass filter, allowing for moving objects to be detected as brighter images.
A smaller value of delta t will allow the detection of smaller moving objects.
A smaller value of delta t will make the computing process more effective, thus allowing for the detection of faster objects.
A larger value of delta t will give a lower sampling rate, allowing for more effective motion tracking.
A larger value of delta t will make slower moving objects appear brighter.
A larger value of delta t is more efficient for tracking the motion of small objects.
A larger value of delta t will act as a high-pass filter, allowing for better detection of fast objects.
Use the 'image subtraction' method to find the average brightness of the image
Use a 'color detection' algorithm to separate the colors in the motion image
Use the 'center of mass' approach to find the center of brightness of the image
Use the 'connected pixel' algorithm to identify the objects in the image