- The accuracy of the implementation of the model
- Number of samples in the dataset (both positive and negative samples)
- Correctness of the dataset ie, whether the dataset contains the objects that are expected to be classified by the model
- Kernel function being used while training the model
What dataset to use for People Detection with HOG & SVM
20 views (last 30 days)
I'm trying to do people detection with HOG & SVM algorithm. I could get maximum 60% accuracy. As I changed the training dataset, the accuracy changes but still can't pass over the %60. You think, is the problem about the dataset or the algorithm?
You can see the code in the following link: https://github.com/mfurkannargul/people-detection-hog-svm-matlab
Pranav Verma on 15 Sep 2020
The accuracy of the model trained depends on a lot of factors.
You can consider using Mdl = fitcsvm(___,Name,Value) where you can define options for kernel and other parameters as name, value pairs.
Similarly, you can use [___] = extractHOGFeatures(___,Name,Value) for defining options as name, value pairs.
For further information on SVM and HOG in matlab, please refer to the following documentation: