[PDF] Top 20 Learning temporal information from spatial information using capsnets for human action recognition

... Fig. 4 shows the confusion matrices of our CapsNet with weight pooling on the KTH and UCF-sports (for 11 actions) datasets. These matrices show that the majority of the ac- tions are classified with high accuracy. It is ... See full document

... Deep Learning Models: Deep learning models [42]–[44] can learn a hierarchy of features by constructing high-level representations from low-level ...deep learning on handwritten digit ... See full document

... the human body from the background so that human actions can be identified in ...the information about temporal motion is broken down into a single image structure as in Figure 2, where ... See full document

... deep learning algorithms such as Convolutional Neural Networks (CNNs) [LeCun et ...and recognition [Lu et ...the action recognition task in videos have been proposed in several recent works ... See full document

... in human visual system, it allows human to focus on important information while ignoring irrelevant ...key information in the image by performing spatial transformation to the ... See full document

... for action recognition can be generally cate- gorized into 2D ConvNet and 3D ...features from sampled RGB frames, which only exploit local spatial information rather than local ... See full document

... has temporal components. To extract temporal features, video action recognition needs to deal with a large number of video frames and get implied ...the temporal as well as the ... See full document

... these spatial features sequentially ...the spatial glimpses are soft-assigned to the workers, such that no hard decisions are made at any point ...by human behavior when scrutinizing a scene, a fixed ... See full document

... is action detected frame. The action detected frame is key ...by using MHI. The MHI contains both spatial and temporal ...classification using SVM. Then each activity is ... See full document

... We employ the dense trajectory features. As dense sam- pling has shown improving results over sparse interest points, the dense trajectory firstly samples the points in different spatial scales densely, then ... See full document

... for action recognition, ...learn temporal motion dynamics but lack effective ways to tackle unsteady dynamics in long-duration ...memory-augmented temporal dynamic learning network, ... See full document

... Human action recognition as one of the most active topics in computer vi- sion has long been in the last few decades, and its potential applications can be found in many important areas such as ... See full document

... face recognition, there are relatively a smaller number of approaches for recognition using multi view ...The recognition algorithm is frame- based PCA and LDA fused by the sum ...clustered ... See full document

... signatures from special images constructed from the ...contains temporal as well as spatial information about the video ...contains spatial and temporal information ... See full document

... of human body are used for activity ...for human activity ...system, human postures (upright standing, move trunk and arms, picking up objects, moving lying down, ...on-line human activity ... See full document

... for health care applications and gaming. Generally, object segmentation on a static camera is done using background subtraction. Background subtraction is used for its simplicity and e ffi ciency [23]. Ideally, ... See full document

... Abstract— Human action recognition is an important research area which has captured lot of attention from the research community due to its significant ...deep learning-based methods ... See full document

... GIScience, spatial masterminding, cartography, programming building, and condition) have comprehended the colossal capacity of OSM and it has transformed into the subject of academic ...of learning made and ... See full document

... richer information (Zheng et al. 2016). The information of different video frames comple- ments each other, so that it is more robust to ...of spatial-temporal information is the key to ... See full document

... However, the fully connected DNN models, they do not capture local dependencies of the time series signals. Thus, some methods utilized the Convolution Neural Network (CNN) [13, 14, 15] which consists of one or more ... See full document