In human-human interaction, three modalities of communication (i.e., verbal, nonverbal, and paraverbal) are naturally coordinated so as to enhance the meaning of the conveyed message. In this paper, we try to create a...
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In human-human interaction, three modalities of communication (i.e., verbal, nonverbal, and paraverbal) are naturally coordinated so as to enhance the meaning of the conveyed message. In this paper, we try to create a similar coordination between these modalities of communication in order to make the robot behave as naturally as possible. The proposed system uses a group of videos in order to elicit specific target emotions in a human user, upon which interactive narratives will start (i.e., interactive discussions between the participant and the robot around each video's content). During each interaction experiment, the humanoid expressive ALICE robot engages and generates an adapted multimodal behavior to the emotional content of the projected video using speech, head-arm metaphoric gestures, and/or facial expressions. The interactive speech of the robot is synthesized using Mary-TTS (text to speech toolkit), which is used - in parallel - to generate adapted head-arm gestures [1]. This synthesized multimodal robot behavior is evaluated by the interacting human at the end of each emotion-eliciting experiment. The obtained results validate the positive effect of the generated robot behavior multimodality on interaction.
We propose a novel method to estimate a unique and repeatable reference frame in the context of 3D object recognition from a single viewpoint based on global descriptors. We show that the ability of defining a robust ...
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For the fast and accurate self-localization of mobile robots, landmarks can be used very efficiently in the complex workspace. In this paper, we propose a simple color landmark model for self-localization and a fast l...
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For the fast and accurate self-localization of mobile robots, landmarks can be used very efficiently in the complex workspace. In this paper, we propose a simple color landmark model for self-localization and a fast landmark detection and tracking algorithm based on the proposed landmark model. We develop a color landmark with a symmetric and repetitive structure, which shows invariant color histogram characteristics under some geometric distortions. Detection and tracking of the model are accomplished by a factored sampling technique in which color similarity is estimated by the color histogram intersection. We also use the color similarity to update the color histogram model of the landmark model for robust tracking under illumination change. We demonstrate the feasibility of the proposed technique through experiments in cluttered indoor environments.
Recently, many global stereo methods have achieved good results by modeling a disparity surface as a Markov random field (MRF) and by solving an optimization problem with various techniques. However, most global metho...
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We study natural human activity under difficult settings of cluttered background, volatile illumination, and frequent occlusion. To that end, a two-stage method for hand and hand-object interaction detection is develo...
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ISBN:
(纸本)9781479909940
We study natural human activity under difficult settings of cluttered background, volatile illumination, and frequent occlusion. To that end, a two-stage method for hand and hand-object interaction detection is developed. First, activity proposals are generated from multiple sub-regions in the scene. Then, these are integrated using a second-stage classifier. We study a set of descriptors for detection and activity recognition in terms of performance and speed. With the overarching goal of reducing 'lab setting bias', a case study is introduced with a publicly available annotated RGB and depth dataset. The dataset was captured using a Kinect under real-world driving settings. The approach is motivated by studying actions-as well as semantic elements in the scene and the driver's interaction with them-which may be used to infer driver inattentiveness. The proposed framework significantly outperforms a state-of-the-art baseline on our dataset for hand detection.
Finding correspondences of two images taken from largely different camera configuration is a challenging problem because appearance information such as color, intensity and edge orientation histogram cannot be used. A...
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Finding correspondences of two images taken from largely different camera configuration is a challenging problem because appearance information such as color, intensity and edge orientation histogram cannot be used. A probabilistic approach to match line segments in the images is proposed for calculating their homography. A membership matrix to represent contribution of every match to the homography is employed. A relaxed version of forward stepwise regression is derived and the test statistic is optimized. An alternating scheme for optimizing the membership and homography is provided. The simulation results on synthetic images validate the proposed method.
On account of having real-time behavior and being easy to implement, spring meshes have been used for modeling deformable objects. Determining spring stiffness parameters for simulation of soft objects with high accur...
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This paper explores the integration of quantum computing, specifically quantum annealing, into robotics for inspecting electrical transmission lines. By using quantum annealing's computational power, we address th...
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In this paper, we present a new social intelligent robotic system used for cognitive stimulation therapy for individuals suffering from Mild Cognitive Impairment (MCI) and/or Alzheimer's disease. Our work aims inc...
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