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Understanding natural human activity involves not only identifying the action being performed, but also locating the semantic elements of the scene and describing the person's interaction with them. We present a system that is able to recognize complex, fine-grained human actions involving the manipulation of objects in realistic action sequences. Our method takes advantage of recent advances in sensors...
This is a qualitative empirical study that contributes to the field human capital and brand innovation in China with regards specifically to the top level management of Chinese grown and owned enterprises. Using a tri-pronged framework of analysis based on grounded theory, critical discourse analysis and visual semiotics, this study focuses in particular on the recent growth of Geely Automobile, that...
We present an approach to automatically learn the visual appearance of an environment in terms of object classes. The procedure is totally unsupervised, incremental, and can be executed in real time. The traversability property of an unseen object is also learnt without human supervision by the interaction between the robot and the environment. An incremental version of affinity propagation, a state-of-the-art...
In this paper, a novel sparse feature representation method for object tracking is proposed. The method is on the observation that a tracked object can be dynamically and compactly represented by a few features (sparse representation) from a large feature set (the improved histogram of oriented gradient and color, HOGC). Based on the HOGC features, the sparse representation can be learned online from...
We describe a model of “trust” in human-robot systems that is inferred from their interactions, and inspired by similar concepts relating to trust among humans. This computable quantity allows a robot to estimate the extent to which its performance is consistent with a human's expectations, with respect to task demands. Our trust model drives an adaptive mechanism that dynamically adjusts the robot's...
The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing the similarity between different subparts. Using this kernel function, together with motor primitive actions, the robot...
This article presents a robust, real-time background subtraction algorithm able to operate properly in complex dynamically changing visual conditions and indoor/outdoor environments, based on a single, cheap monocular camera, like a webcam. This algorithm uses an image grid and models each pixel of the grid as a mixture of adaptive Student-t distributions. This approach makes this algorithm robust...
In this paper we propose a local space-time descriptor to be employed for behaviour analysis in video-surveillance applications. We show how this local video representation is able to extract scene semantics in both a supervised (behaviour recognition) and semi-supervised (anomaly detection) setup. Our approach yields state-of-the art performance on two publicly available datasets and is not computationally...
The study of stabilogram is an important step in postural control analysis. This paper presents an analysis of stabilogram using the mPCA decomposition and shows the effects of different aspects on the human postural stability. The aim of this study is to analyze stabilogram center of pressure time series using the mPCA (modified Principal Analysis Component) decomposition method. This method is suitable...
This paper presents an analysis of the effect of thirteen different kinds of sound on visual gaze when looking freely at videos to help to predict eye positions. First, an audio-visual experiment was designed with two groups of participants, with audio-visual (AV) and visual (V) conditions, to test the sound effect. Then, an audio experiment was designed to validate the classification of sound we...
The study is about the influence of face in videos. In the experiment, the participants were instructed free viewing of various videos. The resulting eye positions are compared to the hand-labeled faces to evaluate the impact of location and number of faces in the visual field. Here, we defined three regions—Inside (I), Periphery (P), and Outside (O)—to categorize video frames with one or two faces...
It is very important to reduce the possibility of spatial disorientation because spatial disorientation is a major cause of aircraft crashes. In this research, we assess the effect of transcutaneous electrical nerve stimulation (TENS) on spatial cognitive function by measuring physiological signals, including brain waves measured by electroencephalography (EEG). Through physiological signals such...
In the research of augmented reality, many experimental systems have been introduced so far by presenting CG objects into a real environment with visual and auditory information, so that a user would interact with the CG objects and the environment. To present higher reality, not only visual and auditory information but also tactile and other stimuli should be presented to users to enhance the perception...
Stereoscopic image quality assessment has been widely studied in last decades; however, the research on 3D quality of experience (QoE) is proposed recently. As a part of human stereo perception, 3D QoE plays an important role to stereoscopic image quality assessment. In this paper, an objective metric is proposed based on the hypothesis that binocular vision system is sensitive to the structure of...
Motion capture data acquired from high definition cameras creates accurate human motion representation but introduces many redundant frames which pose a problem in data storage and motion retrieval purposes. In this paper, a keyframing approach is proposed to reduce the motion data by extracting keyframes using motion analysis approach in sampling windows. Motion changes in sampling windows for original...
Visual saliency detection provides an important methodology for many computer vision applications. In this paper, we propose a novel method to detect salient regions from an image. To detect pixel-level saliency, this method uses joint embedding of spatial and color cues, i.e., spatial constraint based saliency, color double-opponent saliency, and similarity distribution based saliency. Finally, a...
The future of tele-conferencing is towards multi-party 3D Tele-Immersion (TI) and TI environments that can support realistic inter-personal communications and virtual interaction among participants. In this paper, we address two important issues, pertinent to TI environments. The paper focuses on techniques for the real-time, 3D reconstruction of moving humans from multiple Kinect devices. The off-line...
The most eye catching regions within an image or video can be captured by exploiting characteristics within the human visual system. In this paper we propose a novel method for modeling the visual saliency information in a video sequence. The proposed method incorporates wavelet decomposition and the modeling of the human visual system to capture spatiotemporal saliency information. A unique approach...
In this paper, we present an unsupervised learning method, based on the finite Dirichlet mixture model and the bag-of-visual words representation, for categorizing human action videos. The proposed Bayesian model is learned through a principled variational framework. A variational form of the Deviance Information Criterion (DIC) is incorporated within the proposed statistical framework for evaluating...
Aimed at contextual mapping of environments by exploration, this paper proposes a method that recognises human activity observed from a moving camera and references this information to a previously mapped environment. We first introduce a novel method that uses sparse features and dense optical flow, to perform dense background subtraction for an agile camera. With the ego-motion disambiguated, we...
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