Titlebook: Smart Sensing and Context; 5th European Confere Paul Lukowicz,Kai Kunze,Gerd Kortuem Conference proceedings 2010 Springer Berlin Heidelberg

patch-test

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顧客

王得到

Activity Recognition Using Biomechanical Model Based Pose Estimationlassifier. The presented activity recognition techniques are used for recognizing 9 everyday and fitness activities, and thus can be applied for e.g., fitness applications or ‘in vivo’ monitoring of patients.

FLASK

A Formal Model of Reliable Sensor Perceptionpart of the framework then allows for an evaluation of a probabilistic variant of the sensor regarding its safety and precision. We in particular treat the analysis of sensor fusion based on evidence theory.

adipose-tissue

FireGuide: A Context-Aware Fire Response Guide for the Building Occupants guide or museum guide, we ask ourselves: “can we build a context-aware fire guide to assist on-site fire victims to escape from a fire?” In reality, many people lose their lives in fire disasters due to bad judgment. Poor decisions are likely made in urgent situations. Timely and appropriate guidan

輕快帶來(lái)危險(xiǎn)

How to Log Sleeping Trends? A Case Study on the Long-Term Capturing of User Dataoyment. Taking the logging of sleeping postures as an example, this study examines data from two very different modalities, high-fidelity video footage and logged wrist acceleration, that were chosen for their ease of setting up and deployability for a sustained period. An analysis shows the deploym

欺騙世家

Utilizing Social Context for Providing Personalized Services to Mobile Usersable such activities - are increasingly used. This paper describes a system that uses information users share on these networks (personal context), to recommend Web feeds of related content to users. The system mines data from popular social networks and combines it with information from third party

innate

Activity Recognition Using Biomechanical Model Based Pose Estimationated from shoulder and elbow joint angles and torso orientation, provided by upper-body pose estimation based on a biomechanical body model. The recognition performance of signal-oriented and model-based features is compared within this paper, and the potential of improving recognition accuracy by c

REIGN

協(xié)奏曲

On the Use of Magnetic Field Disturbances as Features for Activity Recognition with on Body Sensorsy caused by large metallic objects and electrical appliances, both of which are often involved in human activities. We propose to detect them by subtracting angular velocity values computed from the changes in the magnetic field vector from gyroscope signals. We argue that for activities that are as