Do I Need Pretrained Weights For Keras VGG16?
It would be beneficial to use pretrained weights trained on ImageNet because ImageNet is a huge dataset, and is fairly general. So you're more likely to get good image features from it. You might have to play around with from which layer you want to extract the features from.

If you want to create your own embeddings, you need to use the same code and instead of loading the weights, train it instead on the images you have. I do not recommend this for the following reasons


You most likely have too small a dataset for the model to converge  
VGG16 does classification, what will be the labels for the individual frames is a design choice and being a novice, it might be frustrating for you to get it right
It takes a lot of time and resources, not an ideal situation


P.S, if you still feel that ImageNet does not sufficiently cover your use case, you can try the pretrained Inception V3 model trained on the Open Images dataset