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Inter-subject correspondence is an important aspect of multi-subject fMRI studies. Recently, a new approach, called hyperalignment, has shown very promising results in fMRI functional alignment. Hyperalignment is based on Procrustean rotations and is connected, mathematically, to canonical correlation analysis. We review the core details of each approach, relate them through an SVD analysis, and indicate...
Motion is one of the main characteristics that describe the semantic information of videos. In this work, a global video descriptor based on orientation tensors is proposed. This descriptor is obtained by combining polynomial coefficients calculated for each image in a video. The coefficients are found through the projection of the optical flow on Legendre polynomials, reducing the dimension of per...
Word semantic similarity is a very subjective concept and it is very difficult to get a similarity value close to human judgment. Chinese word semantic similarity research is relatively scarce due to its inherent complexity. This paper presents an approach to compute Chinese word semantic similarity based on statistical methods with word frequency contrast introduced (WFC-WS). Word semantic vectors...
The prediction of HR supply is an important item of HR management in enterprises. This thesis proposes the prediction method of Markov chain, highlights the relevant principle, and indicates the specific application with instances.
GPS is the premier method of localization and way finding in outdoor environments. Indoor environments prevent GPS from functioning properly or at all. RF-based solutions have been proposed using varieties of radio triangulation and spectral fingerprinting. Such technically attractive methods have not seen widespread adoption in places where the demand is greatest: supermarkets, shopping malls, airports,...
In this paper a pattern classification and object recognition approach based on bio-inspired techniques is presented. It exploits the Hierarchical Temporal Memory (HTM) topology, which imitates human neocortex for recognition and categorization tasks. The HTM comprises a hierarchical tree structure that exploits enhanced spatiotemporal modules to memorize objects appearing in various orientations...
In this paper we propose an approach to recognize human actions using depth images. Here, we capture the motion dynamics of the object from the depth difference image and average depth image. The features from the space-time depth difference images are obtained from hierarchical division of the silhouette bounding box. We also make use of motion history images to represent the temporal information...
This paper addresses the problem of extracting perceptually dominant color names of images. Our approach is motivated by the principle that the pixels corresponding to one dominant color name identified by human are often context dependent, spatially connected and form a perceptually meaningful region. Our algorithm first learns the probabilistic mapping from a RGB color to a color name. Then, a double-threshold...
Automatic assessment of image quality in accordance with the human visual system (HVS) finds application in various image processing tasks. In the last decade, a substantial proliferation in image quality assessment (IQA) based on structural similarity has been observed. The structural information estimation includes statistical values (mean, variance, and correlation), gradient information, Harris...
Based on real-value vague sets risk preference score function, this paper presents an approach for determining scoring value of interval vague and applies it to multi-criteria decision making problems. The approach completely embodies risk preference of decision maker as well as the effect of various uncertain information to decision making. Finally, an example is given to illustrate the effectiveness...
Robot imitation is a useful tool in humanoid robot research, it provides a natural way of teaching a complex humanoid robot to accomplish human-like behaviors. However, it is never an easy task to build such a system robustly due to the high degree of freedom (DOF) in human motion and difficulty in humanoid control. In this paper, we present a system built up by the Microsoft Kinect box and the Aldebaran...
Physical human-robot interaction between a human leader and a robot follower in waltz is studied in this paper. The dancers' body dynamics in single-support phase are modeled as inverted pendulums. On the robot side, an ankle torque control method is proposed and applied. The control law forms a time-dependent vector field, which makes the nominal orbit of the robot to be an attractor. To physically...
Local spatiotemporal detectors and descriptors have recently become very popular for video analysis in many applications. They do not require any preprocessing steps and are invariant to spatial and temporal scales. Despite their computational simplicity, they have not been evaluated and tested for video analysis of facial data. This paper considers two space-time detectors and four descriptors and...
In this paper, we propose an improved photometric stereo scheme based on the Lambertian reflectance model and the constrained independent component analysis (cICA) method. When we obtain an object¡¦s surface normal vector on each point of an image using the ICA model to reconstruct 3D shapes, we find that the x-axis, y-axis and z-axis values of the normal vector¡¦s coordinates are not arranged in...
In this paper, we apply Web images to the problem of automatically extracting video shots corresponding to specific actions from Web videos. Our framework modifies the unsupervised method on automatic collecting of Web video shots corresponding to the given actions which we proposed last year [9]. For each action, following that work, we first exploit tag relevance to gather 200 most relevant videos...
One challenge when tracking objects is to adapt the object representation depending on the scene context to account for changes in illumination, coloring, scaling, etc. Here, we present a solution that is based on our earlier approach for object tracking using particle filters and component-based descriptors. We extend the approach to deal with changing backgrounds by using a quick training phase...
This paper proposes a novel system to assist human image analysts to effectively browse and search for objects in a camera network. In contrast to the existing approaches that focus on finding global trajectories across cameras, the proposed approach directly models the relationship among raw camera observations. A graph model is proposed to represent detected/tracked objects, their appearance and...
This paper deals a novel pseudonoise sequence with imperceptibility in conceptually significant region of human auditory system. The proposed sequence was generated from a typical pseudonoise sequence by the canonical signed digit coding and ordered pair transition. Frequency and auto- and cross-correlation analysis were tested for security, randomness and imperceptibility. The proposed sequence is...
In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This new observations inspired us to model saccadic behavior and visual...
In this paper, we present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D skeletal joint locations from Kinect depth maps using Shotton et al.'s method [6]. The HOJ3D computed from the action depth sequences are reprojected using LDA and then clustered into k posture visual words, which represent...
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