Human activity recognition is a crucial domain in computer science and artificial intelligence that involves the Detection, Classification, and Prediction of human activities using sensor data such as accelerometers, gyroscopes, etc. This field utilizes time-series signals from sensors present in smartphon...
The problem of pattern recognition cannot ultimately be separated from that of the organization of action: activity in view of ends. The concept of pattern is essentially relative; ambiguity can be removed only by talking of pattern-for-an-agent. The significance of a pattern for an agent lies...
We introduce a simple yet surprisingly powerful model to incorporate attention in action recognition and human object interaction tasks. Our proposed attention module can be trained with or without extra supervision, and gives a sizable boost in accuracy while keeping the network size and computational...
Acting upon target stimuli from the environment becomes faster when the targets are preceded by a warning (alerting) cue. Accordingly, alerting is often used to support action in safety-critical contexts (e.g., honking to alert others of a traffic situat
The initial two components, which infer 3D information from 2D human skeleton actions and generate spatial transformation parameters to correct abnormal deviations in action data, support the latter in the model to enhance the accuracy of action recognition. The model is designed in an end-to-end,...
An object-oriented approach using a top-down and bottom-up process for manipulative action recognition. volume 4174 - Li, Fritsch, et al. - 2006 () Citation Context ...ard algorithm which needs a clear segmentation of the pattern. Therefore the manipulative primitives can be detected from a ...
The chal- lenges of building video datasets has meant that most popu- lar benchmarks for action recognition are small, having on the order of 10k videos. In this paper we aim to provide an answer to this question using the new Kinetics Human Action Video Dataset [16], which is two ...
Recognizing human actions in video sequences, known as Human Action Recognition (HAR), is a challenging task in pattern recognition. While Convolutional Neural Networks (ConvNets) have shown remarkable success in image recognition, they are not always di
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class-levelobjectdetectioninimages,objectlocalization/(Houghvotes)comingfromlocalimage/elements. trackingthroughs,andactionrecognitionins.Suchaggregationisperformedinaparametricspace(Hough Ourworkisrelatedtoseveralideasreoccurringinthespace),whereeachpointcorrespondstotheexistenceofan literature.First,theideaoflocalappea...