5

There are several approaches as to how this can be achieved. One recent study from 2015 about Action Recognition in Realistic Sports VideosPDF uses the action recognition framework based on the three main steps of feature extraction (shape, post or contextual information), dictionary learning to represent a video, and classification (BoW framework). A few ...


5

This study from 2012 uses 3D convolutional neural networks (CNN) for automated recognition of human actions in surveillance videos. The 3D CNN model extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby capturing the motion information encoded in multiple adjacent frames. A very similar deep learning ...


4

After a bit of research I found something kind of close: Artificially intelligent security cameras are spotting crimes before they happen New surveillance cameras will use computer eyes to find 'pre crimes' by detecting suspicious behaviour and calling for guards CCTV 'fightcams' detect violence 'before it happens' at Dailymail, also check at Telegraph ...


3

MIT have done research and implemented an incomplete version of action video recognition. With the use of MATLAB, NNetworks and a large set of training videos. My suggested set of comments on my previous answer indicate the usage of a multi interconnected NNet, verus MIT's image based NNet.


2

A neural network can be used but must be trained to expect the information (pattern of data, pixels or groupings of loose range such as color, and location) at any given location in the network, first a vision system must but implemented. Then a facial recognition, multiple partial individual body fixing (finding body part and there partners to a person) ...


1

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,...


1

Temporal Depth is a third parameter of a time series data. For example if you have a video clip of length 25 frames and on training a model you are giving first five frames with respect to time. Your temporal depth will be 5.


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I don't know of any work on this with respect to PDDL, but this is very similar to a conceptual dependency application called SAM (Script Applier Mechanism). Conceptual Dependency (CD) models actions using a number of primitives (which could be seen as equivalent to PDDL primitive actions): PTRANS for physical transfer, PROPEL for application of a physical ...


1

This question actually includes many. I try to answer a couple. First of all, you need to make sure for your use case to know the non-functional requirements. It is helpful to know that you have a soft real-time case (if harm is done in case of too late predictions it might also be hard real-time) Latency: how much time may pass after the action was made ...


1

This is an old area of AI called "Plan Recognition", which has about 3.5 million results in Google Scholar. A lot of the modern work is done with classical search techniques coupled with expert domain knowledge, or related reasoning concepts like Hierarchical Task Networks. I'm not aware of or able to find recent research using deep neural networks for ...


1

It is true that at first look, one could expect that classification between 101 categories would be harder than classification between 51 categories. However, many aspects play a role when it comes to action recognition applications. For instance, the HMDB51 contains several categories about different facial movements like smiling, laughing, chewing,... and ...


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