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It seems you need a spatio-temporal model to learn human-body detection and action. With regards to interesting papers on the subject I would recommand to look at Vicky Kalogeiton web site. Her PhD thesis 2017, V. Kalogeiton, Localizing spatially and temporally objects and actions in videos, basically cover her 3 papers on the subject: 2016, Kalogeiton,...


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You will only need to use ML or AI if a) the dataset is very big. b) It is difficult to get the meaning or value of the image.(ex: group of ants, photos of stars in night sky) And many more. Below is the way I thought it can be done through a machine(with deeplearning, CNN) 1. Train the model arrange the images in dataset into clusters (the number ...


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You have not described exactly what the tasks will be, but there are some open source libraries for real time pose tracking. For example, OpenPose is one that can be configured to track the body, the hands and the face. However, this is only going to give you predicted pose information for each frame. If the subjects are meant to be doing specific tasks, e.g....


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Because it is possible to fool many different models at once. See table 2 in this paper, for an example using adversarial perturbations: https://arxiv.org/pdf/1610.08401.pdf That being said, there is no reason to think that using two detectors at once will not increase chance to detect deepfakes. It will just not resolve the problem completely.


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Look at spatio-temporal CNNs which extend the image-based CNN in 2D to 3D to handle time. These are commonly used to detect or classify action in a video. People have used them to identify specific actions in various sports such as kicking a soccer ball, throwing a baseball or dribbling a basketball. They have been used to identify fire, smoke, deep fakes,...


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CNNs are translation invariant. You are over complicating the problem. The easiest thing you can do is define a region of interest (ROI) of the hood. In the first case where the car is moving and the reflections are dynamic. In the second case they are static. Just do frame-to-frame image subtraction of the hood. If the vehicle is moving you will have ...


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