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The number of triangles in a graph is useful to deduce a plethora of important features of the network that the graph is modeling. However, finding the exact value of this number is computationally expensive. Hence, a number of approximation algorithms based on random sampling of edges, or wedges (adjacent edge pairs) have been proposed for estimating this value. We argue that for large sparse graphs...
This paper presents a novel method for interest level estimation based on matrix completion via rank minimization. The proposed method estimates interest levels of target objects from human behavior features which are extracted during selecting these objects. Specifically, by adopting matrix completion via rank minimization, unknown interest levels can be estimated. Furthermore, the proposed method...
This paper presents a new method for video preference estimation using functional near-infrared spectroscopy signals (fNIRS signals). The proposed method first computes fNIRS features from fNIRS signals recorded while users are watching videos and multiple visual features from these videos. Next, by applying Locality Preserving Canonical Correlation Analysis to fNIRS features and each visual feature,...
We propose a model that adapts to CNN trained by non-rotated images even for rotated images by evaluating the feature map obtained from the convolution part of CNN. The additional network for rotation angle estimation is able to correct the rotation angle using the feature map in the MNIST data-set. It is possible to cope with the rotation without changing the original network by adding a network...
Automatic and accurate human upper-body detection and orientation estimation have great practical value in several computer vision applications. Most previous works on human upper-body orientation estimation assume that the human upper-body region is already detected and aligned. However, this is not the case in many real-world scenarios. Additional human detector is essential which is usually much...
For low density crowd, the statistical information of pixels and feature points can reflect the change of crowd density. Therefore, pixels and corners are fused in this paper, then, SVR is used to learn the corresponding relationship between feature and the number of people. While PSO is used to optimize the choice of parameters C and gamma in SVR. The experimental results show that the SVR optimized...
In this paper, we present an improved motion estimation method by adding extra information for binocular visual odometry (VO) which is especially suited for improving high-speed pose change estimation. The extra information is obtained by structured object detecting, taking lane line detection as an example. We can get an accurate position information by calculating the interval of each dotted lane...
In this paper, we propose a position estimation method utilizing image recognition for an automatic traveling wheelchair. The proposed method includes image magnification to extend the recognition distance and image recognition to estimate the position by utilizing a relationship in which the size of the object in an image is inversely proportional to the distance between the camera and the object...
A decision-level fusion (DLF)-based team tactics estimation method in soccer videos is newly presented. In our method, tactics estimation based on audio-visual and formation features is newly adopted since the tactics of the soccer game are closely related to the audio-visual sequences and player positions. Therefore, by using these features, we classify the tactics via Support Vector Machine (SVM)...
In this article, we present an algorithm to track objects in complex environments like, large variations in scale and orientation, background clutters, illumination changes, pose variation and occlusion. A multilayer perceptron based discriminative appearance model is constructed to distinguish the objects from their cluttered backgrounds. Moments of the binary image are used to estimate scale and...
This paper proposes a new method to detect static caption regions using intensity range maps and a statistical model of motion vectors. The method relies on the probability of block-based intensity ranges and magnitudes of motion vectors. Intensity range is used to find candidate locations of static captions and the statistical model of motion vector is used to refine accurate caption regions. The...
This paper presents novel video feature-based favorite video estimation method. In the proposed method, we use three features, videos, users' viewing behavior and users' evaluation scores for these videos. In order to calculate the novel video features, Multiset Canonical Correlations Analysis (MCCA) is applied to these features to integrate the different types of features. Specifically, MCCA maximizes...
The present paper describes a low-cost algorithm for video stabilization. Like other feature based algorithms, it is robust to motion blur, noise and illumination changes. Moreover, maintaining real time processing, it is not negatively affected by moving objects in the scene, works fine even in conditions of low details in the background and it is robust to scene changes.
Classification between foggy and non-foggy images is a primitive step for automation in traffic activity and industries. The existing techniques provide low accuracy and needs validation over both synthetic and natural database. Foggy images are identified and classified based on their optical characteristics for vision enhancement and to make them more efficient for further processing. In proposed...
Depression is considered as a psychosomatic state associated with the soft biometric features. People suffering from depression always behave abnormal. Depression is a clinically proven disorder that can overwhelm a person and his ability to perform even a simple task. Soft biometric provides important information about a person without being enough for their verification because they lack uniqueness...
Steganography is the art of hiding data in data in an untraceable way. Main concern of steganography is hiding the existence of hidden message. Steganalysis is the art and science of detecting hidden messages from stego-systems. It also attempts to find hidden message such as the type of embedding algorithm, the length of the message, the content of the message or the secret key used from the carrier...
The paper considers the composite detection problem where both detection and parameter estimation are of primary interest. Based on a Neyman-Pearson type of formulation, our goal is to find the joint detector and estimator that minimizes a decision-dependent Bayesian estimation risk subject to the detection error probability constraints. The optimal joint solution not only yields lower Bayesian estimation...
The present paper describes a novel adaptive cross correlation technique of face recognition using closed loop discriminator estimation for face detection. All possible variations in the human face can be obtained by scaling and three types of head roll in different planes. We show here that face recognition system comprises face detection and face verification. Feature selection schemes like eigenfaces,...
In this paper we investigate whether human digital fingerprints can be used to estimate human age-groups. To our knowledge, human age-group estimation using digital fingerprints have not been addressed formally. Human age-group estimation can be applied in the areas of online child protection, age based access control or customized services based on estimated age-groups. Motivated by the fact that...
Estimation of distortion in images using reduced reference mode of quality assessment is a reliable approach to develop quality metrics which are in due coherence with human visual system (HVS). This paper proposes a novel reduced reference image quality assessment methodology employing multi-resolution approaches for features extraction. The extracted features are then used to formulate a distortion...
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