In robotics, there has been a growing interest in expressing actions as a combination of meaningful subparts commonly called motion primitives. Primitives are analogous to words in a language. Similar to words put together according to the rules of language in a sentence, primitives arranged with certain rules make an action. In this paper we investigate modeling and recognition of arm manipulatio

The random distribution of features in an iris image texture allows to perform iris-based personal authentication with high confidence. We propose three new iris representations that are based on a multi-scale Taylor expansion of the iris texture. The first one is a phase-based representation that is based on binarized first and second order multi-scale Taylor coefficient. The second one is based

Action representation is a key issue in imitation learning for humanoids. With the recent finding of mirror neurons there has been a growing interest in expressing actions as a combination meaningful subparts called primitives. Primitives could be thought of as an alphabet for the human actions. In this paper we observe that human actions and objects can be seen as being intertwined: we can interp

We address the problem of unsupervised discovery of action classes in video data. Different from all existing methods thus far proposed for this task, we present a space-time link analysis approach which consistently matches or exceeds the performance of traditional unsupervised action categorization methods in various datasets. Our method is inspired by the recent success of link analysis techniq

In the area of imitation learning, one of the important research problems is action representation. There has been a growing interest in expressing actions as a combination of meaningful subparts called action primitives. Action primitives could be thought of as elementary building blocks for action representation. In this article, we present a complete concept of learning action primitives to rec

The representation of human movements for recognition and synthesis is important in many application fields such as: surveillance, human-computer interaction, motion capture, and humanoid robots. Hidden Markov models (HMMs) are a common statistical framework in this context, since they are generative and are able to deal with the intrinsic dynamic variation of movements performed by humans. In thi

This work compares iterative 2D-3D Pose Estimation methods for use in real-time applications. The compared methods are available for public as C++ code. One method is part of the openCV library, namely POSIT. Because POSIT is not applicable for planar 3D-point configurations, we include the planar POSIT version. The second method optimizes the pose parameters directly by solving a Non-linear Least

In humanoid robotics, the recognition and synthesis of parametric movements plays an extraordinary role for robot human interaction. Such a parametric movement is a movement of a particular type (semantic), for example, similar pointing movements performed at different table-top positions. For understanding the whole meaning of a movement of a human, the recognition of its type, likewise its param

The recognition and synthesis of parametric movements play an important role in human-robot interaction. To understand the whole purpose of an arm movement of a human agent, both its recognition (e.g., pointing or reaching) as well as its parameterization (i.e., where the agent is pointing at) are important. Only together they convey the whole meaning of an action. Similarly, to imitate a movement

The transition to symbolic information from images involves in general the loss or misclassification of information. One way to deal with this missing or wrong information is to get feedback from concrete hypotheses derived at a symbolic level to the sub-symbolic (signal) stage to amplify weak information or correct misclas-sifications. This paper proposes such a feedback mechanism between the sym

Syftet var att undersöka arbetsplatsrelationer som resurser för hälsa och välbefinnande från ett salutogent perspektiv. Antalet äldre människor ökar i befolkningen och äldreomsorgen har redan en ansträngd arbetsbörda, varför det är angeläget att ägna mer uppmärksamhet åt de salutogena aspekterna för arbetstagarna inom äldreomsorgen. Studierna utfördes inom en kommunal vård- och omsorgsorganisationThe purpose of this thesis was to explore workplace relations as resources for health and well-being from a salutogenic perspective. The number of elderly people is increasing in the population and elderly care has already a strained workload, why it is urgent to pay more attention to the salutogenic aspects for employees’ in elderly care. The studies have been carried out within a municipal healt

Resting tremors occur in more than 70% of patients with advanced Parkinson's disease (PD). PD patients with resting tremors are typically treated with oral dopaminergic therapy or non-dopaminergic agents. However, treatment response with these medications is inconsistent and often unsatisfactory. Levodopa-carbidopa intestinal gel (LCIG, also known in the United States as carbidopa-levodopa enteral

In Parkinson's disease, pain is a prevalent and complex symptom of diverse origin. King's Parkinson's disease pain scale, assesses different pain syndromes, thus allowing exploration of its differential prevalence and influence on the health-related quality of life of patients. Post hoc study 178 patients and 83 matched controls participating in the King's Parkinson's disease pain scale validation

Levodopa-carbidopa intestinal gel (LCIG, carbidopa-levodopa enteral suspension in the United States) is a treatment option for advanced Parkinson's disease (PD) patients with motor fluctuations. The objective of this investigation was to identify the baseline characteristics predictive of treatment response, measured by improvement in motor symptom severity, in advanced PD patients treated with LC

The recognition of human actions such as pointing at objects ("Give me that...") is difficult because they ought to be recognized independent of scene parameters such as viewing direction. Furthermore, the parameters of the action, such as pointing direction, are important pieces of information. One common way to achieve recognition is by using 3D human body tracking followed by action recognition