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Leaf occlusion is a challenging issue in surveillance video particularly in public outdoor places. The objective of leaf occlusion detection is to automatically determine whether the video suffers from leaf occlusion or not. To tackle this challenge, this paper proposes a learning-based leaf occlusion detection approach, which incorporates a new feature map into a deep learning network. The proposed...
Palm Vein Identification(PVI) systems have been attracting interests from academia, industry, and governments for their advantages such as identification accuracy and relative low costs. However, low cost Infrared (IR) camera sensors produce noisy images which degrades the robustness of these systems. This paper proposes a new PVI system that uses a mirror based stereo camera setup to increase the...
Pedestrian detection is an important key problem in Advanced Driver Assistance Systems (ADAS). Un-signalized pedestrian crossing zone are dangerous places, where pedestrians enter the lane suddenly. This is the main factor for most of the accidents. For that, this paper illustrates a machine learning approach for detecting the pedestrian zone and also to detect the pedestrians crossing in that zone...
Computer vision has become the tool of two-dimensional image recognition and analysis, which mainly means extracting image features. But the problem of robustness and real-time property in complex scenarios makes feature extraction become a challenging task. Visual attention is an important psychological adjustment mechanism in the process of human visual information management, under the guidance...
This paper presents the design and implementation of a Vision based Helipad detection algorithm in an aerial image by image processing techniques. The aerial image obtained from the on board camera of Unmanned Aerial Vehicle (UAV) was processed by several image processing techniques to remove the noise and to segment the helipad. Then this image was matched with a pre-loaded template of the Helipad...
Structure-from-motion (SfM) is a well-studied problem in the computer vision field and is of particular interest for aerial imaging applications like mapping, terrain modeling, crop monitoring, etc. With the current rapid growth in the commercial UAV and small satellite markets, aerial SfM is becoming even more important. In recent years, free and open source software has enabled almost anyone to...
Automated recognition of human activities has received considerable attention within the computer vision community. This is mainly due to the plethora of applications where human activity recognition can be deployed such as smart automated surveillance and human computer interaction. In this research study, a motion descriptor is employed for the extraction of features across consecutive frames for...
In this paper, we propose a temporal stereo disparity estimation method. Conventional stereo disparity estimation methods rely on matching costs regarding computation of intensity or position similarities. However, most applications do not consider the temporal dimension when estimating the disparity. In other words, previous approaches disregard potentially useful disparity information that is already...
Determining relative camera pose is a fundamental task in many computer vision systems. Various algorithms have been proposed for determining relative camera pose from feature correspondences, usually based on point correspondences. These correspondences are commonly found using SIFT and similar feature detectors, and Random Sample and Consensus (RANSAC) is commonly applied to identify and remove...
Many computer vision applications adopting consumer depth cameras have recently received much attention due to the availability at low prices and the potential benefits to provide more useful information, which can result in a higher accuracy (e.g., for object recognition). In this work, to address the problem of drinking activity recognition in vision-based Ambient Assisted Living by using depth...
Vision-based Augmented Reality (AR) techniques rely heavily on Computer Vision algorithms for most of their tasks. It is understood that these algorithms require numerous parameters to function and their values can affect their outputs. Oftentimes the results vary greatly when different parameters were used and as a result, the performance of the AR technique that utilises them varies accordingly...
Understanding human behaviour and activities is a challenging problem in computer vision. In application areas like health care and ambient intelligence, the use of a camera feed might be seen as too invasive and may be resented. Human behaviour understanding can combine images, signals, feature extraction and other machine learning techniques. This paper presents an overview of our technique that...
The present paper analyzes the use of an embedded system-on-a-chip (SoC) platform, integrating a multicore ARM processor with FPGA fabric in a single chip, as a stereo vision pre-processing module, used to retrieve depth information from the features to compose 3D landmark points. The Harris and Stephens corner detector is applied to an image pair acquired from a stereo camera setup using a hardware...
In this paper we implemented a system of fisheye vision (a 360° × 180° visual field) for georeferenced tracking of feature points associated with moving objects in urban scenes. To develop this system: 1. We calibrate the intrinsic parameters of a fisheye camera based on the stereographic model. 2. We propose a geometric model of image formation and adjust the position and orientation parameters using...
The use of unmanned aerial vehicles (UAVs) in civil aviation is growing up quickly, enabling new scenarios, especially in environmental monitoring and public surveillance services. So far, Earth observation has been carried out only through satellite images, which are limited in resolution and suffer from important barriers such as cloud occlusion. Microdrone solutions, providing video streaming capabilities,...
Cylindrical panoramic image mosaic has a severe flaw that the focal length must be known. Our article proposes a new method based on image feature points to calculate the focal length in the process of image mosaic. The observation equations can be gotten from the transmission matrix between stitching images. Then the Bundle Adjustment is used to solve equations and optimize the focal length. The...
We present the first demonstration of establishing mutual attention between an outdoor UAV in autonomous normal flight and an uninstrumented human user. We use the familiar periodic waving gesture as a signal to attract the UAV's attention. The UAV can discriminate this gesture from human walking and running that appears similarly periodic. Once a signaling person is observed and tracked, the UAV...
Camera calibration is a fundamental problem in computer vision community. Already extensive research has been conducted and emerge a large number of excellent calibration algorithm, but there is few studies of automatic calibration system, the camera calibration toolbox for the moment almost use multi-use manual or semi-automatic marking the target area and extracting feature points, inefficient and...
This paper presents a method to analyze crowd with computer vision techniques in virtual environments. To overcome the difficulty of obtaining video evidence in hazard situations, or, to meet the demand of big data for machine learning methods, we attempt to use virtual models to simulate actual ones. To prove the reliability of virtual crowd models we simulated in three situations where people walk...
As the development of robot autonomous navigation, visual odometry gains more and more attention in the last few years. It can estimate the egomotion of a robot by analyzing the changes of the on-board camera view. This paper gives an overview of visual odometry and the development of its key technologies, such as feature detection, description and matching/tracking, camera pose estimation. The advantages...
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