ARTEMIS10
* *Analysis and Retrieval of Tracked Events and Motion in Imagery Streams
* Automatic fish classification for underwater species behavior understanding
* Combining inertial and visual sensing for human action recognition in tennis
* Dense spatio-temporal features for non-parametric anomaly detection and localization
* Emphatic human interaction analysis for cognitive environments
* Enhanced human behavior recognition using HMM and evaluative rectification
* Event detection in video using motion analysis
* Event-based unobtrusive authentication using multi-view image sequences
* Human action recognition with MPEG-7 descriptors and architectures
* Human gesture recognition using 3.5-dimensional trajectory features for hands-free user interface
* Human pose estimation with implicit shape models
* Implicit visual concept modeling in image/video annotation
* Joint multitarget object tracking and interaction analysis by a probabilistic bio-inspired model
* Multi-object particle filter tracking with automatic event analysis
* Multi-sensor registration for objects motion detection
* Real time illumination invariant motion change detection
* Tools for semi-automatic monitoring of industrial workflows
17 for ARTEMIS10
ARTEMIS11
* *Analysis and Retrieval of Tracked Events and Motion in Imagery Streams
* Automatic analysis of composite activities in video sequences using Key Action Discovery and hierarchical graphical models
* Automatic crowd density and motion analysis in airborne image sequences based on a probabilistic framework
* Detecting individual in crowd with moving feature's structure consistency
* High-level situation recognition using Fuzzy Metric Temporal Logic, case studies in surveillance and smart environments
* Learning temporal signatures for Lip Reading
* On improving the robustness of differential optical flow
* On the effect of temporal information on monocular 3d human pose estimation
* People appearance tracing in video by spectral graph transduction
* Reading the signs: A video based sign dictionary
* Spatiotemporally localized new event detection in crowds
* Video scene classification based on natural language description
* Video summarization guiding evaluative rectification for industrial activity recognition
13 for ARTEMIS11
ARTEMIS12
* *Analysis and Retrieval of Tracked Events and Motion in Imagery Streams
* 3D Rotation Invariant Decomposition of Motion Signals
* Constrained Clustering with Local Constraint Propagation
* Destination Flow for Crowd Simulation
* Detecting Interesting Events Using Unsupervised Density Ratio Estimation
* Dynamic Markov Random Field Model for Visual Tracking
* Flow Counting Using Realboosted Multi-sized Window Detectors
* Learn to Move: Activity Specific Motion Models for Tracking by Detection
* Method for Online Analysis of Structured Processes Using Bayesian Filters and Echo State Networks, A
* Mode Seeking with an Adaptive Distance Measure
* Monocular Camera Fall Detection System Exploiting 3D Measures: A Semi-supervised Learning Approach
* Occlusion Handling in Video Segmentation via Predictive Feedback
* Person Identification Using Full-Body Motion and Anthropometric Biometrics from Kinect Videos
* Real Time Detection of Social Interactions in Surveillance Video
* Relative Camera Localisation in Non-overlapping Camera Networks Using Multiple Trajectories
* Spatio-temporal Video Representation with Locality-Constrained Linear Coding
* SuperFloxels: A Mid-level Representation for Video Sequences
* Towards Space-Time Semantics in Two Frames
18 for ARTEMIS12