AIMC Journal:
IEEE transactions on pattern analysis and machine intelligence

Showing 281 to 290 of 300 articles

Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the group-wise least square loss regularized by low rank and spa...

Deep Dynamic Neural Networks for Multimodal Gesture Segmentation and Recognition.

IEEE transactions on pattern analysis and machine intelligence
This paper describes a novel method called Deep Dynamic Neural Networks (DDNN) for multimodal gesture recognition. A semi-supervised hierarchical dynamic framework based on a Hidden Markov Model (HMM) is proposed for simultaneous gesture segmentation...

Minimum Entropy Rate Simplification of Stochastic Processes.

IEEE transactions on pattern analysis and machine intelligence
We propose minimum entropy rate simplification (MERS), an information-theoretic, parameterization-independent framework for simplifying generative models of stochastic processes. Applications include improving model quality for sampling tasks by conc...

Nonparametric Feature Matching Based Conditional Random Fields for Gesture Recognition from Multi-Modal Video.

IEEE transactions on pattern analysis and machine intelligence
We present a new gesture recognition method that is based on the conditional random field (CRF) model using multiple feature matching. Our approach solves the labeling problem, determining gesture categories and their temporal ranges at the same time...

Modeling 3D Environments through Hidden Human Context.

IEEE transactions on pattern analysis and machine intelligence
The idea of modeling object-object relations has been widely leveraged in many scene understanding applications. However, as the objects are designed by humans and for human usage, when we reason about a human environment, we reason about it through ...

Labeled Graph Kernel for Behavior Analysis.

IEEE transactions on pattern analysis and machine intelligence
Automatic behavior analysis from video is a major topic in many areas of research, including computer vision, multimedia, robotics, biology, cognitive science, social psychology, psychiatry, and linguistics. Two major problems are of interest when an...

HAKE: A Knowledge Engine Foundation for Human Activity Understanding.

IEEE transactions on pattern analysis and machine intelligence
Human activity understanding is of widespread interest in artificial intelligence and spans diverse applications like health care and behavior analysis. Although there have been advances with deep learning, it remains challenging. The object recognit...

Parsing Based on Parselets: A Unified Deformable Mixture Model for Human Parsing.

IEEE transactions on pattern analysis and machine intelligence
Human parsing, namely partitioning the human body into semantic regions, has drawn much attention recently for its wide applications in human-centric analysis. Previous works often consider solving the problem of human pose estimation as the prerequi...

Human-Machine CRFs for Identifying Bottlenecks in Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence
Recent trends in image understanding have pushed for scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape analysis, contextual reasoning, and local appearance based classifiers. In this...

Anticipating Human Activities Using Object Affordances for Reactive Robotic Response.

IEEE transactions on pattern analysis and machine intelligence
An important aspect of human perception is anticipation, which we use extensively in our day-to-day activities when interacting with other humans as well as with our surroundings. Anticipating which activities will a human do next (and how) can enabl...