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Accurately characterizing linearity performance of high resolution Analog-to-Digital Converters (ADCs) has been a challenging task for many years, as providing input signals whose purity is beyond ADC under test becomes harder and harder as the ADC performance becomes better. This paper proposes a novel method that uses impure test signals to accurately test linearity performance of ADC. Two nonlinear...
In this paper, the comparison of a novel key-point image descriptors such as DAISY, BRISK, A-KAZE and LATCH with the well-known SIFT and SURF descriptors are tested and compared for the stereo matching algorithm. The main idea of this paper is to present an independent, comparative study and some of the benefits and drawbacks of these most popular image descriptors on stereo images. These descriptors...
For traditional computer vision methods the analysis of motion and behaviours in crowded scenes constitutes a challenging task, as barriers like occlusions, varying crowd densities and complex stochastic nature of their motions are difficult to overcome. As it has to be kept within reasonable limits, the one more complicating factor is the computational cost. It is very crucial to analyse crowded...
Detection of Shot boundary is the fundamental step in the video analysis. In many applications such as video indexing, summarization and retrieval, shot boundary detection plays a major role. It serves as a preliminary step to construct the content of videos. Boundary detection involves identification of frames at which the content of scene is significantly different. In this paper, an integrated...
Recently, Content Based Image Retrieval (CBIR) has received a great attention by researchers. It becomes one of the most interesting topic in computer vision and image processing. CBIR image can be represent by local or global features. The entire image is described in the case of global features by using a novel descriptor called Upper-Lower of Local Binary Pattern (UL-LBP) based on Local Binary...
Object tracking is a challenging problem in computer vision as many performance affecting factors need to be considered in a robust algorithm. We propose a framework to consolidate Integral Channel Features (ICF) to represent targets' appearance by embedding global and patch based approaches which offer feature strength and accuracy to the target template. The use of ICF expedites the extraction of...
Single face-image comparisons are extremely challenging, particularly in the context of pose, expression variations and scene illumination changes. Most of the existing schemes are sub-space learning based, where dominant eigen-directions are determined from the covariance matrix computed over the entire face space. In this paper we propose a simple hashing method based on the relative magnitudes...
This paper presents a novel quantized gradient based local feature descriptor, named Local Quantized Gradient Direction (LQGD) descriptor and the subsequent Partitioned Gradient Histogram, for facial image representation. The 8 bit LQGD descriptor accommodates eight levels quantized gradient magnitude and direction information from the horizontal and vertical gradients at local facial image pixels...
We present a novel means of describing local image appearances using binary strings. Binary descriptors have drawn increasing interest in recent years due to their speed and low memory footprint. A known shortcoming of these representations is their inferior performance compared to larger, histogram based descriptors such as the SIFT. Our goal is to close this performance gap while maintaining the...
In the new Steganographic technique, hiding is based on the difference between the secret message value and the pixel value of the green component of the image. The proposed method works in the spatial domain of the image. We check the difference value between secret byte ASCII (American Standard Code for Information Interchange) value and the pixel ASCII value. For comparison embedding is initially...
In this paper, we propose a feature representation that achieves translation, rotation, and scale invariant simultaneously. We first proposed a novel component, called Block Based Integral Image, to search the densest region of feature points. This aims to find the center of potential object in the image. Then, with the improved object center, we apply Spatial Pyramid Ring (SPR) by to handle translation...
We analyze gestures for the initialization of HCI system, such as ‘hand-shaking’ and ‘hand-pushing’, especially in the aspects of robustness and sensing methods. For the detection of derived ‘hand-pushing’ action, temporal variation of depth histogram is used. The proposed method is empirically verified.
In robot perception, as well as in other areas of 3-D computer vision, keypoint detection is the first major step for an efficient and accurate 3-D perception of the environment. Thus, a fast and robust algorithm for an automatic identification of keypoints in unstructured 3-D point clouds is essential. The presented algorithm is designed to be highly parallelizable and can be implemented on modern...
In this paper we describe a novel digital image watermarking method using local binary patterns (LBP). Local binary patterns are known for their robust texture describing capabilities and digital watermarking used in proving the ownership of a multimedia content. In this work we propose a LBP synthesis or inverse LBP matching process and its applicability to digital image watermarking. LBP synthesis...
Combining multiple observation views has proven beneficial for pedestrian tracking. In this paper, we present a methodology for tracking pedestrians in an uncalibrated multi-view camera network. Using a set of color and infrared cameras, we can accurately tracking pedestrians for a general scene configuration. We design an algorithmic framework that can be generalized to an arbitrary number of cameras...
We consider linear programs where some parameters in the objective functions are unknown but data are available. For a risk-averse modeler, the solutions of these linear programs should be picked in a way that can perform well for a range of likely scenarios inferred from the data. The conventional approach uses robust optimization. Taking the optimality gap as our loss criterion, we argue that this...
A near-duplicate video clustering algorithm based on multiple complementary video signatures is proposed in this work. We use three kinds of frame descriptors: RGB histogram, color name histogram, and ternary pattern. Then, we convert each kind of frame descriptors for a video into a video signature based on the bag-of-visual-words scheme. Consequently, we have three signatures to represent the video...
We show that holistic image features, specifically GIST, can be used for semantic scene categorization. In our study, the problem of indooroutdoor scene classification is addressed. We first propose a simple yet efficient pipeline in which the GIST vector of an image is initially computed. For the classification task, a feedforward neural network is trained with a comprehensive training dataset. The...
Feature extraction methods have an important role in image classification. In this paper, a hybrid texture feature descriptor is proposed by utilizing the attributes of two complementary features, PRICoLBP and LPQ. PRICoLBP performs well in the case of geometric and photometric variations however it does not properly express the local texture of an image, while LPQ method performs well for the local...
Empirical Centroid Fictitious Play (ECFP) is a generalization of the well-known Fictitious Play (FP) algorithm designed for implementation in large-scale games. In ECFP, the set of players is subdivided into equivalence classes with players in the same class possessing similar properties. Players choose a next-stage action by tracking and responding to aggregate statistics related to each equivalence...
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