Deep Learning Computer Vision Interview Series #4-Asked In Interview ⭐ ⭐⭐⭐⭐⭐⭐⭐

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[damodharratnamthappeta]

since the model retraining is not possible, may be changing the lens which has more focus and then it will be able to capture it from that height

[akashchoudhuri]

Sir, please start a Computer-Vision Playlist

[sivasai]

If we kept the camera higher from original position the object size will be decreased and some times our model may not recognize it.Then i think we can zoom the camera like appearimg from old position then it may work 🤔 and of course we should use good resolution camera

[peterr]

The simplest answer would be if the existing model is orientation invariant, there is nothing to change. Otherwise, a certain orientation compensation needs to be done such as homography, or perspective transformation.

[vivekkandeyang]

We can try preprocessing the image such that the distribution at the new position matches the old. Though preprocessing will not fix the things completely but we will definitely get closer results.

[ganeshkolnure]

Using calibration matrices(intrinsic+extrinsic parameter) we can transform image from new(new height) coordinate system to old (old position height) coordinate system..

[saravanans]

By including some sort of lens that would compensate for the reduction in the size of the car due to the change in height?

[kaiwalyagondchar]

Firstly we calculate the Max distance between camera and the object at which model will perform efficiently using stereo vision and then we can add a constraint that the object detection will work within that perticular distance.

[dv]

1. Change the threshold 1st. 2. Use deep sort or you can say a tracker, integrate it to your model (pertained version easily available)

[sumannelli]

We can use object tracking concept...there which pixels are moving we need to scaleup those part..thanks

[ArunKumar-tuln]

We can take the ratio of image height and width with respect to height of camera, hence the change in height of camera will be compensated as ratio is taken, instead of original.

[tejach]

The major change would the change in perspective of the camera
We can use homography to obtain the images similar to the previous position of the camera

[raviyadav]

sir pls make a series on computer vision.

[somnathroy]

One can use SAHI Slicing to predict the outputs, basically it slices the image in overlapping windows with a prefixed stride and calculate model prediction for each of the slices then combines the results applying IOU to get the final results.

[gauravchaudhari]

I got IISC Mtech AI offer can you please take interview with student or review of the course I am comparing with MTech cs in other IIT's

[nuzhat_tasfia]

Hello Krish. I am a beginner in computer vision. It's my humble request to make a computer vision playlist from scratch in google colab. Please Krish its a request. We really need it. No one can explain beautifully as you do. Please Krish..🙏🙏

[asqwer]

I'd focus on creating an argument parser and set my threshold to x as the default. (70%).
From their, if I have to relocate the camera to a higher point, and then readjust the threshold within my argument parser to a lower number (40-50% confidence) and see how the model now performs.
I'd focus on first ensuring the model localizes the object, then focus on the classification of that object until my model gets a close enough output that I desire.

[prasannavenkatesh]

After changing the angle it may affect on detection accuracy.
We can try the affine transformation of the image before passing to the model. It may help but without seeing the exact scenario it's hard for drawing the solutions.

Similar problem I have faced. I have to detect the keypoints of the person but the camera view was very much tilted so before passing the frames to the model I've shifted the frame to -40 degree.
After rotating with -40 degree the results were good.

Very much eager to see the approach

[mouryasashank]

This problem is called Concept Drift or Data Drift. It is solved by Periodically Re-Fit, Periodically Update, Weight Data, Learn The Change, Detect and Choose Model, Data Preparation.

[zeeshansheikh]

By Considering some of the Post-processing techniques.

1. Based on the height w.r.t aspect ratio calculating the original ratio of area of interest and we can crop it then zoom the image to get the original region. (here while cropping we can exclude the extra region which is in focus and which is not useful).
note: why crop then zoom? why not zoom and crop?
--> after zooming and then cropping we may loose some pixel values so the best approach is to crop then zoom.

2. Even then we are facing any blur or noise in the image we can use the below techniques to enhance the image.
--> Sharpening the image and smoothening the values with different kernel sizes.
--> Using Image Enhancement techniques or point processing techniques based on contrast.

3. Or else if we have a lens which is cable of getting the focus region from the lens.(Don't know much about iot integration with respect to lens)