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It has been shown in previous studies that haptic guidance improves the learning outcomes of handwriting motor skills. In this paper, we present a comparison between full guidance and partial guidance using a haptic learning tool which supports these two modes. The full guidance mode leads the user along a pre-recorded trajectory, whereas the partial guidance mode allows the user a free movement and...
3Sergey Levine is with Google Brain, Mountain View, CA 94043, USA. We present a policy search method for learning complex feedback control policies that map from high-dimensional sensory inputs to motor torques, for manipulation tasks with discontinuous contact dynamics. We build on a prior technique called guided policy search (GPS), which iteratively optimizes a set of local policies for specific...
In human action classification task, a video must be classified into a pre-determined class. To cope with this problem, we propose a mid-level representation, in which information about quantization errors is embedded together with the aggregated data on low level features. The main contributions of this article are twofold: (i) assembly of low-level features (dense trajectories) by a mid-level representation...
In this work, we decompose a first-person action into verb and noun. We then study how the coupling of an action's constituent verb and noun affects the learners' ability to learn them separately and to combine them to perform recognition. We compare different information fusion methods on conventional action recognition and zero-shot learning, of which the latter is a strong indication of the feature's...
In this paper, we propose a mutual framework that combines two state-of-the-art visual object tracking algorithms. Both trackers benefit from each other's advantage leading to an efficient visual tracking approach. Many state-of-the-art trackers have poor performance due to rain, fog or occlusion in real-world scenarios. Often, after several frames, objects are getting lost, only leading to a short-term...
Haptic guidance has previously been employed to improve human performance in control tasks. This paper presents an experiment to evaluate whether haptic feedback can be used to help humans learn a compensatory tracking task. In the experiment, participants were divided into two groups: the haptic group and the no-aid group. The haptic group performed a first training phase with haptic feedback and...
The paper presents a method for developing illusionary flight profiles situations for practical testing of pilots using the GYRO IPT II spatial disorientation simulator. Standard flight profiles do not use the full capability of the simulator to train pilots for recognition and recovery from illusions appearing unexpectedly. For this reason, there is a need to create new flight profiles so as to demonstrate...
This paper discusses the problem of one shot gesture recognition. This is relevant to the field of human-robot interaction, where the user's intentions are indicated through spontaneous gesturing (one shot) to the robot. The novelty of this work consists of learning the process that leads to the creation of a gesture, rather on the gesture itself. In our case, the context involves the way in which...
Due to the diversity of body movements and uncertainty of recording occasion, human action recognition is still a challenging task, especially in real world. This paper provides a new method of representing the video with mid-level vision representation which is extracted from the discriminative supervoxels. In the proposed method, the discriminative supervoxels we extracted through a learning phase...
This paper presents a novel method for learning a pose lexicon comprising semantic poses defined by textual instructions and their associated visual poses defined by visual features. The proposed method simultaneously takes two input streams, semantic poses and visual pose candidates, and statistically learns a mapping between them to construct the lexicon. With the learned lexicon, action recognition...
This article is focused on possibilities of an implementation of information technologies in a learning of self-defense. The self-defense is a field which is more and more necessary in our life. During our research, we tried to find out if it is possible to connect information technologies with learning of self-defense for more effective results. We used VICON system for visualization of body motion...
Here we explore a visual display technique for low frame rate virtual environments called low persistence (LP). This involves displaying the rendered frame for a single display frame and blanking the screen while waiting for the next frame to be generated. To gain greater knowledge about the LP technique, we have conducted a user study to evaluate user performance and learning during a dynamic target...
In the automatic analysis of a tennis game, it is important to detect some anomalous match events, such as "fault serve" and "ball out", as these events are crucial in understanding the progress of a game. Audio information can be used to detect these events, but it is unreliable, because of the acoustic mismatch between the training and the test data and interfering noise caused...
In this paper, a new kind of Fisher Vector (FV) model, named Scale FV (ScaleFV), is proposed to ameliorate visual feature encoding for human action recognition. Although several researches have been proposed for feature encoding, the temporal scale information is almost ignored. Similar to the spatial scale information which has shown to be important in extracting and encoding visual features, the...
We propose a video graph based human action recognition framework. Given an input video sequence, we extract spatio-temporal local features and construct a video graph to incorporate appearance and motion constraints to reflect the spatio-temporal dependencies among features. them. In particular, we extend a popular dbscan density-based clustering algorithm to form an intuitive video graph. During...
Repetitive retraining of grip function is critical for stroke patients to regain functional abilities. Therefore, we have developed ‘GripAble’, a low-cost but sensitive hand-grip promoting independent and repetitive rehabilitation of grasp function based around a novel flexible structure. An initial usability study was performed on (N = 34) healthy subjects to compare user interaction between this...
Pelvic motion plays an important role in human locomotion. Any abnormality of the pelvic motion during walking, such as asymmetry or altered range of motion, can affect gait stability and energy consumption [1]. In this work, we propose a new control methodology to guide and correct the human pelvic motion in the transverse plane during walking. An assist-as-needed paradigm was used to generate forces...
There is an initial body of work that compared the effectiveness of robotic strategies that amplify or reduce movement errors on motor learning. However, these comparative studies still show inconclusive results, probably because they searched for the robotic strategy that enhances learning, independently of the subjects' skill level and the specific characteristics of the task to be learned. Some...
To detect an event which is defined by the interaction of objects in a video, it is necessary to capture their spatio-temporal relation. However, the video only displays the original 3D space which is projected onto a 2D image plane. This paper introduces a method which extracts 3D trajectories of objects from 2D videos. Each trajectory represents the transition of an object's positions in the 3D...
Error feedback is critical for supporting motor adaptation in rehabilitation, sports, piloting, and skilled manual tasks. Error augmentation interventions, in which participants' errors are amplified with either visual or haptic feedback during training has shown success over repetitive practice. Here we show that the statistical tendencies arising from free movement exploration can improve error...
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