Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 22 for “"Human Action Recognition"”.
-
Towards practical automated human action recognition
… requires addressing high-level concepts such as humans' actions and activities. Automated human action recognition is an interesting research area, as well as one of the main trends in the automated video survei1lance industry. The typical goal of action recognition is that of labelling an image …
-
Human Action Recognition in Still Images
Recently still image-based human action recognition has become an active research topic in computer vision and pattern recognition. It focuses on identifying a person's action or behavior from a single image. Unlike the traditional action recognition approaches where videos or image sequences are …
-
Human action recognition with 3D convolutional neural networks
… recently developed elements to present a human action recognition model which is up-to-date with current trends in CNNs and current hardware. Focus is applied to ensemble models and methods such as the Dropout technique, developed by Hinton et al. (2012) to reduce overfitting, and learning …
-
Hybrid architecture for human action recognition using skeleton data
… in skeleton based multi-person, multiview human action recognition. By leveraging attention-based GCN, the model captures context-dependent intrinsic topology while enhancing discriminative information. Furthermore, utilizing transformers, we harness their ability to aggregate long-range …
-
Vision-based human action recognition using machine learning techniques
The focus of this thesis is on automatic recognition of human actions in videos. Human action recognition is defined as automatic understating of what actions occur in a video performed by a human. This is a difficult problem due to the many challenges including, but not limited to, variations in …
-
Human action recognition in the real world: handling domain shift in open-set, source-free and multi-source scenarios
Human behavior understanding as an application of artificial intelligence and deep learning has quickly acquired popularity over the past few years, due to the crucial role it plays in trending fields such as human-robot interaction, autonomous driving, drone footage, sports and video surveillance. …
-
Human and Animal Behavior Understanding
Human and animal behavior understanding is an important yet challenging task in computer vision. It has a variety of real-world applications including human computer interaction (HCI), video surveillance, pharmacology, genetics, etc. We first present an evaluation of spatiotemporal interest point …
-
Learning Privacy-Preserving Transferable Video Representations
… datasets has become essential to achieve high action recognition performance on smaller downstream datasets. However, most large-scale video datasets are accompanied with issues related to privacy, ethics, and data protec-tion, often preventing them to be publicly shared with the community for …
-
Three-Dimensional Face Processing and Its Applications in Biometrics
… (3) the non-frontal-view face/facial expression recognition/human action recognition, which is among the earliest efforts of the research communities in this area.
-
Structured video content analysis : learning spatio-temporal and multimodal structures
… and text, there is multimodal structure, e.g., human behavioral data shows correlation between audio (speech) and visual information (gesture). Identifying, formulating, and learning these structured patterns is a fundamental task in video content analysis. This thesis tackles two challenging …
-
Human activity analysis using radio signals
Understanding people's actions and interactions typically depends on seeing them. Automating the process of human action recognition and event captioning from visual data has been the topic of much research in the computer vision community. But what if it is too dark, or if the person is occluded …
-
Sequential Recognition of Manipulation Actions Using Superpixel Group Mining
Human action recognition is one of the important research areas in computer vision. Manipulation action recognition which contains complex human-object interactions is a challenging problem in this area. Especially for the manipulation actions in the kitchen scenario, occlusions among objects and …
-
View-Invariance in Visual Human Motion Analysis
… solutions to two problems in the area of visual human motion analysis: human action recognition and human body pose estimation. Although there has been a substantial amount of research addressing these two problems in the past, the important issue of viewpoint invariance in the representation and …
-
Human detection and action recognition using depth information by Kinect
… by Kinect to address the issues regarding human detection and action recognition. Taking the depth information, the basic problem we consider is to detect humans in the scene. We propose a model based approach, which is comprised of a 2D head contour detector and a 3D head surface detector. …
-
Recognizing simple human actions by exploiting regularities in pose sequences
The human visual system represents a very complex and important part of brain activity, occupying a very significant portion of the cortex resources. It enables us to see colors, detect motion, perceive dimensions and distance. It enables us to solve a very wide range of problems such as image …
-
Robust Real-Time Recognition of Action Sequences Using a Multi-Camera Network
Real-time identification of human activities in urban environments is increasingly becoming important in the context of public safety and national security. Distributed camera networks that provide multiple views of a scene are ideally suited for real-time action recognition. However, deployments …
-
Action Recognition with Knowledge Transfer
… on deep neural networks has shown remarkable action recognition performance from videos. The remarkable performance is often achieved by transfer learning: training a model on a large-scale labeled dataset (source) and then fine-tuning the model on the small-scale labeled datasets (targets). …
-
Shape Dynamical Models for Activity Recognition and Coded Aperture Imaging for Light-Field Capture
Classical applications of Pattern recognition in image processing and computer vision have typically dealt with modeling, learning and recognizing static patterns in images and videos. There are, of course, in nature, a whole class of patterns that dynamically evolve over time. Human activities, …
-
Im2Vid: Future Video Prediction for Static Image Action Recognition
Static image action recognition aims at identifying the action performed in a given image. Most existing static image action recognition approaches use high-level cues present in the image such as objects, object human interaction, or human pose to better capture the action performed. Unlike …
Page 1 of 2