Section: New Results

Introduction

This year Stars has proposed new results related to its three main research axes : perception for activity recognition, semantic activity recognition and software engineering for activity recognition.

• Exploring Depth Information for Head Detection with Depth Images (see 6.2)

• Modeling Spatial Layout of Features for Real World Scenario RGB-D Action Recognition (see 6.3)

• Multi-Object Tracking of Pedestrian Driven by Context (see 6.4)

• Pedestrian detection: Training set optimization (see 6.5)

• Pedestrian Detection on Crossroads (see 6.6)

• Automated Healthcare: Facial-expression-analysis for Alzheimer's patients in Musical Mnemotherapy (see 6.7)

• Hybrid Approaches for Gender estimation (see 6.8)

• Unsupervised Metric Learning for Multi-shot Person Re-identification (see 6.9)

• Semi-supervised Understanding of Complex Activities in Large-scale Datasets (see 6.10)

• On the Study of the Visual Behavioral Roots of Alzheimer's disease (see 6.11)

• Uncertainty Modeling with Ontological Models and Probabilistic Logic Programming (see 6.12)

• A Hybrid Framework for Online Recognition of Activities of Daily Living In Real-World Settings (see 6.13)

• Praxis and Gesture Recognition (see 6.14)

• Scenario Recognition (see 6.15)

• The clem Workflow (see 6.16)

• Safe Composition in Middleware for Internet of Things (see 6.17)

• Verification of Temporal Properties of Neuronal Archetype (see 6.18)

• Dynamic Reconfiguration of Feature Models (see 6.19)

• Setup and management of SafEE devices (see 6.20)

• Brick & Mortar Cookies (see 6.21)