Human action recognition from various data modalities: A review
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …
each action. It has a wide range of applications, and therefore has been attracting increasing …
Learning in audio-visual context: A review, analysis, and new perspective
Sight and hearing are two senses that play a vital role in human communication and scene
understanding. To mimic human perception ability, audio-visual learning, aimed at …
understanding. To mimic human perception ability, audio-visual learning, aimed at …
CAD-contextual multi-modal alignment for dynamic AVQA
In the context of Audio Visual Question Answering (AVQA) tasks, the audio and visual
modalities could be learnt on three levels: 1) Spatial, 2) Temporal, and 3) Semantic. Existing …
modalities could be learnt on three levels: 1) Spatial, 2) Temporal, and 3) Semantic. Existing …
Advances in human action recognition: an updated survey
SAR Abu‐Bakar - IET Image Processing, 2019 - Wiley Online Library
Research in human activity recognition (HAR) has seen tremendous growth and
continuously receiving attention from both the Computer Vision and the Image Processing …
continuously receiving attention from both the Computer Vision and the Image Processing …
Event detection in soccer videos using unsupervised learning of spatio-temporal features based on pooled spatial pyramid model
Most existing researches for semantic analysis of soccer videos benefit from special
approaches to bridge the semantic gap between low-level features and high-level events …
approaches to bridge the semantic gap between low-level features and high-level events …
A comparative analysis of decision-level fusion for multimodal driver behaviour understanding
Visual recognition inside the vehicle cabin leads to safer driving and more intuitive human-
vehicle interaction but such systems face substantial obstacles as they need to capture …
vehicle interaction but such systems face substantial obstacles as they need to capture …
Deep learning based human action recognition: A survey
Z Zhang, X Ma, R Song, X Rong, X Tian… - 2017 Chinese …, 2017 - ieeexplore.ieee.org
Human action recognition has attracted much attentions because of its great potential
applications. With the rapid development of computer performance and Internet, the …
applications. With the rapid development of computer performance and Internet, the …
Still image action recognition based on interactions between joints and objects
Still image-based action recognition is a challenging area in which recognition is performed
based on only a single input image. Utilizing auxiliary information such as pose, object, or …
based on only a single input image. Utilizing auxiliary information such as pose, object, or …
Non-linear consumption of videos using a sequence of personalized multimodal fragments
As videos progressively take a central role in conveying information on the Web, current
linear-consumption methods that involve spending time proportional to the duration of the …
linear-consumption methods that involve spending time proportional to the duration of the …
Modselect: Automatic modality selection for synthetic-to-real domain generalization
Modality selection is an important step when designing multimodal systems, especially in
the case of cross-domain activity recognition as certain modalities are more robust to …
the case of cross-domain activity recognition as certain modalities are more robust to …