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Captchas are frequently used on the modern world wide web to differentiate human users from automated bots by giving tests that are easy for humans to answer but difficult or impossible for algorithms. As artificial intelligence algorithms have improved, new types of Captchas have had to be developed. Recent work has proposed a new system called Avatar Captcha, in which a user is asked to distinguish...
A method is described for preventing unauthorized copying of information shown on a display. It utilizes the difference in spectral sensitivity between humans and imaging devices. A near-infrared light source, which has no effect on human vision, is installed in front of an existing display to corrupt the content of photographs taken of the display. Testing using a prototype implementation demonstrated...
Automatic detection and recognition of traffic signs is an important tool in intelligent vehicles. It allows more autonomous vehicles and it can alert the driver to possible hazards and changes in the road. In this paper we focus on the recognition of a wide set of triangular traffic signs using a novel algorithm, the Number of Peaks. Once a traffic sign is detected, three horizontal lines (T, H,...
Motivated by models of human decision making, we consider a heuristic solution for explore-exploit problems. In a numerical example we show that, with appropriate parameter values, the algorithm performs well. However, the parameters of the algorithm trade off exploration against exploitation in a complicated way so that finding the optimal parameter values is not obvious. We show that the optimal...
The segmentation of MR images is of great interests in automatic medical diagnosis. However, such images are corrupted by Rician noise and with fuzzy edges. The non-additive and intensity dependant features of Rician noise make image processing very challenging. In this paper, a combination of techniques are carefully selected, tailored, and organized to improve the image quality for automatic segmentation...
Foreground extraction and moving object detection are often used in human tracking systems. However those methods are not able to produce accurate results when objects are too close or when occlusions happen since the result is generally a single big blob which contains all the different objects. In this paper we propose a novel and efficient moving object detection enhancement method. Indeed, by...
This paper shows a method of WDR (wide dynamic range) in camera. When we make a digital WDR, commonly we meet two problems. The first one is an increase of noise. And the other is a lot of control factors. In this paper we will show a WDR with low noise and small number of control factors. The circuit is very simple and needs no memory. So the chip size is nearly unchanged after implementation. When...
We propose a method to judge a walker's intention around pedestrian lights by using fuzzy rules. We detect pedestrian object in a movie of crosswalk area by using the code book method and acquire contour information. To improve the processing speed in this stage, we use parallel processing technique based on CUDA (Compute Unified Device Architecture). Now, we remove shadow which causes shape distortion...
This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target...
Realistic modeling of the movement of people in an environment is critical for evaluating the performance of mobile wireless systems such as urban sensing or mobile sensor networks. Existing human movement models are either fully synthetic or rely on traces of actual human movement. There are many situations where we cannot perform an accurate simulation without taking into account what the people...
Proactive physical robotic assistance in the presence of human prediction uncertainty is a very challenging control problem. In this paper we propose a risk-sensitive optimal feedback controller for physical assistance that autonomously adapts the robot's behavior even during unknown situations. Using a probabilistic model to represent the cooperative task execution behavior and modeling the human...
This paper presents an audio monitoring system for detecting and identifying people engaged in a conversation. The proposed method is hands-free as it uses a microphone array to acquire the sound. A particularity of the approach is the use of a laser range finder based human tracker system. The human tracker monitors the locations of people then local steered response power is used to detect the people...
Robot localization is a key barrier to providing natural interaction between 3D virtual characters, human users and mobile robots. Knowing where the robot is, relative to a known world-frame, is essential to directed gestures, gazes and expressions between the robot and the other real and virtual participants in a telepresence system. The intrinsic noise of robots is a flexible and robust, yet under-examined,...
Vehicle license plate recognition has complex characteristics due to diverse effects as the fog, rain, shadows, irregular illumination conditions, partial occlusion, variable distances, cars' velocity, scene's angle and others. License-plate location in sensor images plays an important role in vehicle identification for automated transport systems. For the extraction of positioning in license plate...
We investigate the use of human metrology for the prediction of certain soft biometrics, viz. gender and weight. In particular, we consider geometric measurements from the head, and those from the remaining parts of the human body, and analyze their potential in predicting gender and weight. For gender prediction, the proposed model results in a 0.7% misclassification rate using both body and head...
In this paper, we describe Object Pixel Mixture Classifiers (OPMCs) which classify an object not only apart from background but also from other objects based on Gaussian Mixture Model (GMM) classification. The proposed OPMC is different from general GMM based classifiers in the respect that novel pairwise threshold is applied for final classification. Pairwise thresholds are different thresholds depending...
Uses CAPTCHA in web page can to a certain extent, to resist the attacks from network. But many sites using the CAPTCHA is based on the English or the digital characters, and only adopts a simple deformation treatment, safety not guaranteed. The Chinese CAPTCHA in upper case characters, and adding noise, deformation processing, the machine automatically recognizes the very difficult. The experiment...
One critical issue in indoor human tracking is the design of map-aid algorithms that exploit indoor layout information. Most of current works adopt similar map-aid calibration techniques that eliminate invalid particles, which means particles propagating in inhumane manner. However, we find that these techniques have two serious problems in common, which we name acute sample impoverishment and observation...
Image co-occurrence has shown great powers on object classification because it captures the characteristic of individual features and spatial relationship between them simultaneously. For example, Co-occurrence Histogram of Oriented Gradients (CoHOG) has achieved great success on human detection task. However, the gradient orientation in CoHOG is sensitive to noise. In addition, CoHOG does not take...
This paper deals with a post-processing phase of automatic transcription of spoken documents stored in the large Czech Radio audio archive (containing hundreds of thousands of recordings). The ultimate goal of the project is to transcribe them and to allow public access to their content. In this paper we focus on methods and algorithms for unsupervised post-processing of automatically recognized recordings...
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