In this paper we address two issues concerning real world time-continuous emotion detection from videos of users’ faces: (i) the impact of weak ground truth on the emotion detection accuracy and (ii) the impact of the users’ facial expressiveness on the emotion detection accuracy. We implemented an appearance based emotion detection algorithm that uses Gabor features and nearest neighbors classifier. We tested the performance of this algorithm on two datasets with different ground truth strengths (a firm ground truth dataset and a weak ground truth dataset). Then we split the dataset into three subsets reflecting different levels of users’ facial expressiveness (low, mid and high) and performed separate emotion detection.
COBISS.SI-ID: 9919060
Affective labeling of multimedia content has proved to be useful in recommender systems. In this paper we present a methodology for the implicit acquisition of affective labels for images. It is based on an emotion detection technique that takes as input the video sequences of the users' facial expressions. We performed a comparative study of the performance of a content based recommender (CBR) system for images that uses three types of metadata to model the users and the items: (i) generic metadata, (ii) explicitly acquired affective labels and (iii) implicitly acquired affective labels with the proposed methodology. The results show that the CBR performs best when explicit labels are used.
COBISS.SI-ID: 9586260
Electric powered aircraft has been designed and flown for quite a while. However, until 2011 all the existing models had one major drawback, namely, a low range caused by the low energy capacity of the batteries. Besides the motor and motor controller, the battery system is one of the most critical components of the electric aircraft. Lightweight, high efficiency and high reliability are only a few challenges in the design process. The paper describes the battery system and a new active battery balancing method used for the Taurus G4 of the Pipistrel manufacture, the world's first four-seat electric aircraft, that won the 2011 Green Flight Challenge competition for being the most energy efficient aircraft ever built.
COBISS.SI-ID: 9693524
In this paper we present an application called Med-reminder, which extends the functionality of existing devices providing interactive TV and helps to increase the quality of life for the elderly. The Med-reminder application is used to remind people to take their medicines correctly and on time or to call a relative or a medical person in an emergency situation. Since the graphical user interface was adapted for the elderly,Med-reminder is easy to use without previous training. For evaluating the graphical user interface, navigation and the general usability of the application, and hence the identification of key aspects that increase the adoption rate of assisted living applications among the target population, a methodology for a user evaluation study was designed and conducted. User evaluation study results are presented in the paper.
COBISS.SI-ID: 15703062
We present an intuitive, implicit, gesture based identification system suited for applications such as the user login to home multimedia services, with less strict security requirements. The term “implicit gesture” in this work refers to a natural physical hand manipulation of the control device performed by the user, who picks it up from its neutral motionless position or shakes it. For reference with other related systems, explicit and well defined identification gestures were used. Gestures were acquired by an accelerometer sensor equipped device in a form of the Nintendo WiiMote remote controller. A dynamic time warping method is used at the core of our gesture based identification system. To significantly increase the computational efficiency and temporal stability, the “super-gesture” concept was introduced, where acceleration features of multiple gestures are combined in only one super-gesture template per each user. User evaluation spanning over a period of 10 days and including 10 participants was conducted. User evaluation study results show that our algorithm ensures nearly 100 % recognition accuracy when using explicit identification signature gestures and between 88 % and 77 % recognition accuracy when the system needs to distinguish between 5 and 10 users, using the implicit “pick-up” gesture. Performance of the proposed system is comparable to the results of other related works when using explicit identification gestures, while showing that implicit gesture based identification is also possible and viable.
COBISS.SI-ID: 10034516