To extract "deep features" from a video file like , you typically use a pre-trained Deep Neural Network (DNN) to process the video frames and output high-level numerical representations (embeddings). These features are used for tasks like action recognition, video retrieval, or forensic analysis. Common Deep Feature Extraction Methods
[1611.07715] Deep Feature Flow for Video Recognition - arXiv mfnweB4.mp4
: These represent "what" is in each frame (objects, scenes). You can use a 2D Easy Video Deep Features Extractor (GitHub) to run a network like ResNet or VGG on individual frames and save the results as a .npy (NumPy) array. To extract "deep features" from a video file
Depending on your goal, you can extract features focused on spatial content, temporal motion, or file structure: or file structure: