Human proximity tracking and human situation inference are exploited for comprehending human interaction with objects in kitchen. The importance of this study is to offer interactive and personalized kitchen environment for elderly and disabled people. Also, this smart environment allows for independent living for elderly and disabled people. This study proposes human proximity tracking and inf...

We explore the way in which people look at images of different semantic categories (e.g., handshake, landscape), and directly relate those results to computational approaches for automatic image classification. Our hypothesis is that the eye movements of human observers differ for images of different semantic categories, and that this information can be effectively used in automatic content-bas...

The surveillance system has been developed for decades. It has reduced the crime andprotected the lives and properties of people successfully. Some surveillance systems are composed ofPTZ cameras. Therefore the moving people or target objects could be tracked by the surveillancesystem. The surveillance system becomes more and more interment. However, there are twoproblems occurr...

We explore the way in which people look at images of different semantic categories (e.g., handshake, landscape), and directly relate those results to computational approaches for automatic image classification. Our hypothesis is that the eye movements of human observers differ for images of different semantic categories, and that this information can be effectively used in automatic content-bas...

Tracking the activity of people in indoor environments has gained considerable attention in the robotics community over the last years. Most of the existing approaches are based on sensors which allow to accurately determine the locations of people but do not provide means to distinguish between different persons. In this paper we propose a novel approach to tracking moving objects and their id...

In dealing with a dynamic world, people have the ability to maintain selective attention on a subset of moving objects in the environment. Performance in such multiple-object tracking is limited by three primary factors-the number of objects that one can track, the speed at which one can track them, and how close together they can be. We argue that this last limit, of object spacing, is the roo...

Thanks to the diffusion of wearable devices there are several indoor tracking systems. Among them, RF-based have been deeply studied for their flexibility and limited costs. These systems can be employed as assistive tools only being dependable, identifying faults. We propose two methods to provide multiuser tracking with concurrent localization of natural hardware and human-made faults. The fi...

The object of this paper is to present a set of techniques integrated into a low-lost eye tracking system. Eye tracking systems have many potential applications such as learning emotion monitoring systems, drivers' fatigue detection systems, etc. In this paper, we report how we use an eye tracking system to implement an "eye mouse" to provide computer access for people with severe disabilities....

People tracking is one major part of visual surveillance systems. A number of different people trackers exist nowadays. One of those multi-people trackers is the Reading People Tracker. It consists of four individual co-operating tracking modules. Weaknesses of one module are thereby compensated by the strengths of another one. The Motion Detector performs background-foreground segmentation to ...

This paper proposes a fast and robust multi-people tracking algorithm for mobile platforms equipped with a RGB-D sensor. Our approach features an efficient point cloud depth-based clustering, an HOG-like classification to robustly initialize a person tracking and a person classifier with online learning to manage the person ID matching even after a full occlusion. For people detection, we make ...