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Despite significant progress in pedestrian detection has been made in recent years, detecting pedestrians in crowded scenes remains a challenging problem. In this paper, we propose to use visual contexts based on scale and occlusion cues from detections at proximity to better detect pedestrians for surveillance applications. Specifically, we first apply detectors based on full body and parts to generate...
One of the classical problem in dynamics and control theory, which has being widely used as a benchmark for testing control algorithms, such as Linear Quadratic Regulator (LQR) is the balancing of inverted pendulum. The performance of LQR depends largely on the design choice of state and control weighting matrices (Q & R). However, these matrices are usually selected by the designer through a...
In recent years, the vast images with user-provided tags are easily available on the photo-sharing platform, which can greatly promote image retrieval and management. However, these tags often are incomplete and noisy, impeding the tag related image applications. To address this challenge, a Sparsity Constrained Low-Rank Matrix Completion (SCLRMC) model is proposed for simultaneously completing and...
In this paper, we propose an approach based on the use of artificial fish swarm algorithm (AFSA) for solving the problem of multicast routing on application layer. Taking delay, stretch, and degree as three optimization objectives, we design the behaviors of artificial fish individual (AF), i.e. moving randomly, preying, following, and use Pareto ranking to evaluate the fitness of AF. The simulation...
Nowadays, communication between people is mediated by technology and more specifically via Internet either by using email or social networking sites. Since any online activity generates an electronic trace, creating an automated tool to collect and analyze the communication between people can be valuable for extracting useful information about their behavioral characteristics. Combining these characteristics,...
This paper presented a SIFT based multiple instance learning algorithm to deal with the problem of pose variation in the tracking process. The MIL algorithm learns weak classifiers by using instances in the positive and negative bags. Then, a strong classifier is generated by powerful weak classifiers which are selected by maximizing the inner product between the classifier and the maximum likelihood...
In this modern life, the digital images are being considered the main source of information sharing. The digital images are being used in various fields such as medical imaging, news reporting, crime investigation, insurance claims etc. However, in the presence of sophisticated image editing tools, the credibility of digital images is the main concern. The copy-move forgery (CMF) is a most popular...
Multimedia semantic concept detection is an emerging research area in recent years. One of the prominent challenges in multimedia concept detection is data imbalance. In this study, a multimedia data mining framework for interesting concept detection in videos is presented. First, the Minimum Description Length (MDL) discretization algorithm is extended to handle the imbalanced data. Thereafter, a...
Image segmentation is a key preprocessing step for object recognition and has a profound effect on the subsequent classification and recognition. Visual spatial clustering based segmentation is a commonly used method in image segmentation, which clusters pixels using visual descriptors by space similarity measure. It can achieve good results in simple image segmentation with less noise. This paper...
The diffusion of oil slick is very fast. There are speckle noises and vague boundaries in PolSAR image of oil slick, how to distinguish and mark the continuous edges of oil slick quickly is the basic requirement of oil slick monitoring service. This paper presents a new edge tracing algorithm, which implements the edge tracing of oil slick based on multi-feature fusion. Based on the polarimetric feature...
Wearable cameras are increasingly used in many different applications from law enforcement to medicine. In this paper1, we consider an application of using a wearable camera to record one-on-one therapy with a child in a classroom or clinic. To protect the privacy of other individuals in the same environment, we introduce a new visual privacy paradigm called privacy bubble. Privacy bubble is a virtual...
The ability to obtain a compact description of an object and to keep the significant information can be crucial for many applications such as indexing, clustering and classification. Formal concept analysis (FCA) provides an algorithm to perform such dimension reduction. However, the requirements of FCA limit its performance. In order to relax FCA requirements, this paper presents an extension of...
Herein, we explore both a new supervised and unsupervised technique for dimensionality reduction or multispectral sensor design via band group selection in hyperspectral imaging. Specifically, we investigate two algorithms, one based on the improved visual assessment of clustering tendency (iVAT) and the other based on the automatic extraction of “blocklike” structure in a dissimilarity matrix (CLODD...
This paper presents the results obtained by NSGA-II and jDEMO on a restaurant design optimization in the conceptual phase. A multi-objective problem is formulated by considering the minimization of investment and the maximization of customer count and maximization of visual perception, subject to several constraints. The main problem requires the configuration of restaurant spaces with different seating...
Although the graph-based machine learning has received considerable attention in the remote sensing area and it has been widely used for terrain classification, the construction of graph in most existing algorithms still takes large memory and plenty of computational time especially for large Polarimetric Synthetic Aperture Radar (PolSAR) data. Addressing these issues, we propose a fast semi-supervised...
To solve the problem of poor robustness and low effectiveness of visual tracking in complex scenes, a novel target tracking algorithm based on adaptive observation weight is proposed in this paper. First of all, a weighted observation model is established by linear visual tracking representation. Then an iterative optimization algorithm is proposed to obtain the parameters of the model, and adaptively...
When analyzing news videos, finding an efficient way of extracting visual memes is very important. Videos might be very long and visual meme extraction itself is computationally expensive, so it is essential to make this process as efficient as possible. A way to do this is to eliminate as many key frames as possible even before extracting the visual memes. Since anchor person frames contribute little...
A measurement method for the evaluation of the image complexity based on SIFT&K-means algorithm, namely the estimation of the mismatch between the target and the interesting points has been introduced in our previous research. Based on this method, we have made some improvements to calculate the image complexity of images with different memory targets. The improved algorithm SIFT&AIM&K-means...
EDA tools paved the way for the integration of billion of components in a single integrated circuit. However, many tools still rely on text interfaces. The use of visualizations tools can help not only to provide a visual output of an EDA tool but also to show how a tool is performing in terms of quality of results. A good graphic output can be useful to improve algorithms or develop new ones. Some...
We present a no-reference (NR) image quality assessment (IQA) algorithm that is inspired by the representation of visual scenes in the primary visual cortex of the human visual system. Specifically, we use the sparse coding model of the area V1 to construct an overcomplete dictionary for sparsely representing pristine (undistorted) natural images. First, we empirically demonstrate that the distribution...
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