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Proceedings of the AAAI Conference on Artificial Intelligence
This paper outlines a proposal regarding the use of machine learning, specifically a long-short term model, to increase the military’s effectiveness and safety protocols. The approach is to collect data from weapons training and apply it to a model that can distinguish between weapon activities.
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This paper outlines a proposal regarding the use of machine learning, specifically a long-short term model, to increase the military’s effectiveness and safety protocols. The approach is to collect data from weapons training and apply it to a model that can distinguish between weapon activities.
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Egocentric Activity Recognition on a Budget
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018Recent advances in embedded technology have enabled more pervasive machine learning. One of the common applications in this field is Egocentric Activity Recognition (EAR), where users wearing a device such as a smartphone or smartglasses are able to receive feedback from the embedded device. Recent research on activity recognition has mainly focused on
Rafael Possas +2 more
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Kinesiologic electromyography for activity recognition
Proceedings of the 6th International Conference on PErvasive Technologies Related to Assistive Environments, 2013This paper presents a wearable system based on kinesiologic electromyography that recognizes the user activity in real time. In particular, the system recognizes the following five activities: "walking", "running", "cycling", "sitting" and "standing". We conducted a study in order to select the opportune muscles and sensors placement.
Maurizio Caon +5 more
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Hierarchical Models for Activity Recognition
2006 IEEE Workshop on Multimedia Signal Processing, 2006In this paper we propose a hierarchical dynamic Bayesian network to jointly recognize the activity and environment of a person. The hierarchical nature of the model allows us to implicitly learn data driven decompositions of complex activities into simpler sub-activities.
Amarnag Subramanya +3 more
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Active rangefinding and recognition with Cubicscope
1996An active rangefinding using the Cubicscope is described in the paper. The following topics are reviewed: the principle of the Cubicscope, 3-D shape reconstruction by multiple range images obtained from actively selected viewpoints, high-speed edge detection from range image, and polyhedral object recognition by adaptive viewpoint selection.
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Deep Learning for Sensor-based Human Activity Recognition
ACM Computing Surveys, 2022Bin Guo, Lina Yao, Dalin Zhang
exaly
A Survey on Deep Learning for Human Activity Recognition
ACM Computing Surveys, 2022Shahrokh Valaee +2 more
exaly
Human Activity Recognition: A review
2022 10th International Symposium on Digital Forensics and Security (ISDFS), 2022João Gonçalo Pereira +1 more
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