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An automated approach is proposed which can analyze ground reaction force data from bipedal walking robots and humans. The input of the automated analysis is the raw data from force sensors mounted in the feet of a robot. The output is detailed information, such as detected single support, double support, and swing phases, their durations, timings of events like heel strikes, properties of the phase...
Although leg joint trajectories during human walking show variance in each step it has been reported that the variance of the toe position is suppressed by joint synergy at some critical points to realize stable walking, e.g., at the moment when the toe passes through the nearest position from the ground during leg swing. Is such joint synergy generated by the central nervous system (CNS) or by the...
In human body pose estimation, manifold learning is a useful method for reducing the dimension of 2D images and 3D body configuration data. Most commonly, body pose is estimated from silhouettes derived from images or image sequences. A major problem when applying manifold estimation, however, is its vulnerability to silhouette variation. In this paper, we propose a novel approach to solving viewpoint-induced...
Robot localization is a key barrier to providing natural interaction between 3D virtual characters, human users and mobile robots. Knowing where the robot is, relative to a known world-frame, is essential to directed gestures, gazes and expressions between the robot and the other real and virtual participants in a telepresence system. The intrinsic noise of robots is a flexible and robust, yet under-examined,...
This paper proposes a human movement trajectory recording method by a thermopile array sensor. In the system, the sensor is attached to the ceiling and it acquires place-dependent temperatures, which is called thermal distribution. The system obtains 4 × 4 pixels thermal distributions from the sensor. The distributions are analyzed to extract human movement trajectory. First, human candidate pixels...
This paper proposes a classification system for human activity using a multi-sensor system with a built-in electrocardiograph and 3D accelerometers. The multi-sensor system unconstraintly measures biological information, and provides these data to personal computer by wireless communication. We classify human activity by the biological information. The sensor detects the electrocardiogram and triaxial...
Most of the works in the field of teleoperation of humanoid robots do not use the whole-body of the robot to perform some task. This work treats the teleoperation of a humanoid robot through the recognition of human motions by using a natural interface mechanism. We propose the use of simple mathematical techniques to allow, in a satisfactory level, the user order in real-time a robot to mimic a person,...
This work presents human-inspired control strategies required for achieving three motion primitives in walking—flat-ground, uneven terrain and up-slope—in an underactuated physical bipedal robot: AMBER. Formal models and controllers which provably guarantee the stability of walking are developed and verified in the simulation. Computationally tractable conditions are given that allow for the experimental...
This paper presents a method for achieving stable “human-like” running in simulation by using human-inspired control. Data from human running experiments are processed, analyzed and split into the two domains: stance phase and flight phase. By examining this data, we present a set of outputs, i.e., functions of the kinematics, which appear to represent human running; moreover, we show that this output...
In this article we introduce the C-Model of Interaction between humans and Digital Media1 we empirically researched and analyzed in learning scenarios (workshops). In our trienal research project called “Subject Formation and Digital Culture” (SKUDI) we arranged and designed a series of constructivist and constructionist workshops. In these workshops dealing with robots, smart textiles, fabrication...
We propose a nighttime pedestrian detection method for a moving vehicle equipped with a camera and the near-infrared lighting. The objects in the nighttime environment will reflect the infrared projected. In some cases, however, the clothes absorb most of the infrared and make the pedestrian partially invisible in that part. To deal with this, a part-based pedestrian detection method according to...
This paper focuses on monocular-video-based stationary detection of the pedestrian's intention to enter the traffic lane. We propose a motion contour image based HOG-like descriptor, MCHOG, and a machine learning algorithm that reaches the decision at an accuracy of 99 % within the initial step at the curb of smart infrastructure. MCHOG implicitly comprises the body language of gait initiation, especially...
This position paper proposes a design approach for a "human diminishing device" to generate much more realistic experience of being the physically challenged, such as hemiplegic patients, in comparison to existing simulation suits, and refers to significance of the ghuman diminishing deviceh to let an able-bodied person rediscover its ability gcoveredh in daily life and exploit the ability...
The ability to track, detect and monitor human activities in real time conditions is very important for security and surveillance operation. The movements of the human body and limbs generate unique microDoppler features which enable the identification and classification of a wide diversity of human motions. In this paper, we propose a method to simulate the signal generated by human motion, by modeling...
Pedometers are increasingly being used for purposes like assessment of physical activity, rehabilitation, disease management and as a utility for the visually impaired. These devices rely on algorithms that consist of measuring distance covered by the number of steps taken. Conventional estimations of distance covered rely on empirically obtained relations to arrive at their data. In this paper, we...
The psychological overcharge issue related to human inadequacy to maintain a constant level of attention in simultaneously monitoring multiple visual information sources makes necessary to develop enhanced video surveillance systems that automatically understand human behaviors and identify dangerous situations. This paper introduces a semantic human behavioral analysis (HBA) system based on a neuro-fuzzy...
When human locomotion is used to interact with virtual or augmented environments, the system's immersion could be improved by providing reliable information about the user's walking intention. Such a prediction can be derived from tracking data to determine the future walking direction. This paper analyses how tracking data relates to navigation decisions from an egocentric view in order to achieve...
Human gait is the main activity of daily life. Gait can be used for applications like human identification (in medical field etc). Since gait can be perceived from a distance it can be used for human identification. Gait recognition means identifying the person with his/her gait. Human identification using gait can be used in surveillance. A method is proposed for gait recognition using a technique...
This experiment investigated the kansei information and movement characteristics that observers use to perceive expressions of joy in dance. Expressing joy with movements by dancers was recorded. Observers then rated words related to kansei and characteristics of the movements. The results of factor analyses and multiple regression analyses indicated that the expression of joy in dance has particular...
Previously, research on gait control has mainly focused on interpersonal synchrony and locomotor control. However their intersection, the interpersonal synchronization of stepping rhythms which is widely observed in our daily life, remains relatively unexplored, despite being a common phenomenon that has considerable rehabilitation potential. Therefore, from the perspective of mutual entrainment of...
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