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Plenty of video stuff is created, broadcasted, shared and stored each and every day by industry experts, beginners, and hobbyists. Video summaries aim at showcasing the semantics and content of a clip in reduced time and space to enable a quick overview of video clip relevance. This paper focuses on static summaries showing key frames from the video. The key frames are extracted by leveraging the...
Recently a new set consisting of six information theory features was proposed for on-line signature verification by Rosso, Ospina and Frery. The proposed features were evaluated on the MCYT-100 on-line signature database resulting in the best performance ever measured on that dataset. In this paper we repeat their measurements and show that their result is erroneous. In addition, we evaluate the performance...
Visual tracking is a challenging problem in computer vision, especially when the camera platform is moving. To track a target pedestrian from a UAV (Unmanned Aerial Vehicle) mobile platform, multiple techniques, such as motion control of UAV, visual detection and tracking are needed. This study presents a new tracking method, which mainly involves object tracking, pedestrian detection and online color...
This paper present a query-by-example word spotting in handwritten Arabic documents, based on Harris detector and Scale Invariant Feature Transform (SIFT), without using any text word or line segmentation approach, because any errors affect to the subsequent word representations. First, the interest points are automatically extracted from the images using Harris detector, then, we use SIFT descriptor...
The relative radiometric calibration is essential to get high-quality remote sensing images. An efficient way to bypass the quest of uniformity is to use the satellite agility in order to align the ground projection of the scanline on the ground velocity. This weird viewing principle(side-slither) allows all the detectors to view the same landscape. A relative radiometric calibration model based on...
Here, evaluate the abasement in execution of well known and effective face detector when human captured picture quality is corrupted by additive gaussian noise and blur. It is observed that, inside a specific scope of recognized picture quality, an adequate increase in picture quality can improve face detection performance. These results can be utilized to guide data transfer capacity which regards...
The color and gradient based sequential state estimation method has proved its applicability in many video based tracking applications. This paper proposes a multi-modal approach applicable to trajectory formation of multiple moving objects with complex random motion structure. The Bayesian framework for tracking is formulated in this paper that incorporate spatio temporal information in selecting...
In advanced semiconductor-process technology, the ability to detect and repair lithography hotspots, which can affect printability, is essential. In this paper, we propose a two-stage cascade classifier for accurate hotspot detection. Our classifier uses a novel layout feature based on the propagation of light passing through a photomask. We performed experiments to evaluate our cascade classifier...
The performance of an object detection system relies heavily on two components: an object model to capture the compositional relationship among the object body and its parts, and a feature representation to describe object appearance. In this work, we present an empirical study of combining two state-of-the-art such components: Deformable Part Model (DPM), a proven effective and flexible part-based...
We model dyadic (two-person) interactions by discriminatively training a spatio-temporal deformable part model of fine-grained human interactions. All interactions involve at most two persons. Our models are capable of localizing human interactions in unsegmented videos, marking the interactions of interest in space and time. Our contributions are as follows: First, we create a model that localizes...
In this paper, a novel dense stereo matching algorithm is proposed based on edge-aware truncated minimum spanning tree (T-MST). Instead of employing non-local cost aggregation on traditional MST which is only generated from color difference of neighbouring pixels, a new tree structure, "Edge-Aware T-MST", is proposed to aggregate the cost according to the image texture. Specifically, cost...
A great deal of features detectors and descriptors are proposed every years for several computer vision applications. In this paper, we concentrate on dense detector applied to different descriptors. Eight descriptors are compared, three from gradient based family (SIFT, SURF, DAISY), others from binary category (BRIEF, ORB, BRISK, FREAK and LATCH). These descriptors are created and defined with certain...
This paper investigates the effects of sampling on action recognition performance. Currently, dense (regular grid) sampling and uniform random sampling are popular strategies that achieve state-of-the-art performance. However, they are data-blind and pay equal attention to locations of different informativeness. In this paper, a Shannon information based adaptive sampling approach is proposed for...
Tattoos have been increasingly used as a discriminative soft biometric for people identification, such as criminal and victim identification in forensics investigation and law enforcement. However, automatic detection of tattoo images and accurate localization of the regions of interest are challenged by the large variations in artistic composition, color, shape, texture, location on the body, local...
This paper proposes a novel patient-specific approach to channel selection and seizure detection based on estimating the histograms of multi-channel scalp electroencephalography (sEEG) signals. It consists of two main phases: training and testing. In the training phase, the signal is segmented into non-overlapping 10-second segments, with five histograms estimated for each segment. These histograms...
Searching through and selecting data sets from large traffic databases with sensor information is often a cumbersome manual process. In this paper we present an idea that may dramatically fasten and streamline this process. The idea is to build a fast search index (COSI: COngestion Search engIne) based on meta data in combination with features from the traffic patterns along routes. Instead of ploughing...
Speed Up Robust Features SURF is one of the most popular and efficient methods used for image registration task. In order to achieve a correct registration, a good matching of feature point is required. However in the case of multimodal images, the high and non-linear intensity changes between different modalities led to many outliers (mismatching of detected points) and consequently a fail in the...
Human detection in digital videos is challenging since the human appearance may widely vary. Several algorithms to detect humans in digital images have been recently developed, such as the Aggregated Chanel Features (ACF). Most of them are based on features related to the shape. These algorithms give the best results regarding accuracy but generate many false alarms. In this paper, we propose to use...
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. Image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper...
In this paper we propose a method for automatic collimation border rotation angle detection. Algorithm utilizes pooling of image gradients based on their orientations to form a histogram of oriented gradients (HOG) with the goal of determining the dominant gradient orientation in the image as collimation border rotation angle. To avoid accumulation of lower magnitude gradients only a percentage of...
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