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How to video classification using feature extraction

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Kong on 27 Mar 2020
Answered: Shishir Singhal on 9 Apr 2020
Hello. I want to classify videos using several feature extraction.
I used HOG(histogram of oriented gradients), optical flow as feature extraction.
However, the accuracy of classification is not good. just 60% accuracy.
Could you give some ideas to improve accuracy?
This code is using HOG.
clear all
close all
%// read the video:
list = dir('*.avi')
% loop through the filenames in the list
for k = 1:length(list)
reader = VideoReader(list(k).name);
vid = {};
while hasFrame(reader)
vid{end+1} = readFrame(reader);
for i=1:25
fIdx(i) = i; %// do it for frame 1 ~ 60
frameGray{i} = rgb2gray(vid{fIdx(i)});
[featureVector{i},hogVisualization{i}] = extractHOGFeatures(frameGray{i});
X = cell2mat(featureVector');

  1 Comment

Kenta on 28 Mar 2020
related to your question, a video classification with CNN and LSTM would be very effective.
Pls find the example code below.

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Accepted Answer

Shishir Singhal
Shishir Singhal on 9 Apr 2020
For video classification, you can use CNN for extracting spatial features. CNN is capable to extract deep features that HOG and other handcrafted feature extraction techniques might not be albe to. Use LSTM for capturing temporal features beacause you also need to have some sequential information between frames in a video.
You can read about CNN and LSTM in links here :


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