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The tracking and labeling of multiple objects in multiple cameras is a fundamental task in applications such as video surveillance, autonomous driving, and sports analysis. In an ad-hoc multi-camera network without a fusion center nodes can benefit from local cooperation to solve signal processing tasks, such as distributed image enhancement. A crucial first step for the successful cooperation of...
The lane marking detection task is an essential process in the field of semi-autonomous and autonomous navigation. This paper proposes a method that combines the color and edge information to robustly detect the lane marking within the image either located far on near to the vehicle. Firstly, the region of interest is extracted from the image. Secondly, the set of lane marking features are extracted...
In this paper, we propose an unsupervised technique for the detection of flooded areas using images acquired by a fixed-wing unmanned aerial vehicle (UAV). The proposed methodology for the detection of the flooded areas considers the development of an algorithm based on k means clustering and texture analysis using co-occurrence matrix.
Clustering product features is the essential task to mine opinions from unstructured online reviews because different customers usually express the same feature with different words or phrases. Several supervised and unsupervised methods have been applied to accomplish this task. In this paper, we propose an orthogonal nonnegative matrix tri-factorizations model to solve the problem. We first construct...
Online human action recognition has broad application prospect in many fields of computer vision. Simultaneously, with the advent of depth camera, it brings on a new trend of online human action recognition but still present some unique challenges. In this paper, to solve the lower accuracy of the existing online human action recognition algorithm based on depth camera, we adopt the improved Dynamic...
Automation techniques have been applied in almost every field in past few years. Automated Guided Vehicle (AGV) are most often used in industries and inventories for object management. Obstacle avoidance being a necessary requirement for navigation in any vehicle, still faces many challenges in the field of automation due to uncertain nature of the surrounding environment. This paper presents the...
Video summary technology has become a hotspot of current researches. The application of sports video summary can quickly fetch important information in sports video that help sports enthusiasts and sports senior analysis the video. The present study takes tennis video as the research object. Firstly, determine the number of key frames based on statistical rules, and then extract key frames from different...
Pedestrian detection is paramount for advanced driver assistance systems (ADAS) and autonomous driving. As a key technology in computer vision, it also finds many other applications, such as security and surveillance etc. Generally, pedestrian detection is conducted for images in visible spectrum, which are not suitable for night time detection. Infrared (IR) or thermal imaging is often adopted for...
A new approach to autonomously detect and track moving objects in a video captured by a moving camera from a UAV in real-time is proposed in this paper. The introduced approach replaces the need for a human operator to perform video analytics by autonomously detecting moving objects and clustering them for tracking purposes. The effectiveness of the introduced approach is tested on the footage taken...
Analysis of crowd behaviour in public places is an indispensable tool for video surveillance. Automated detection of anomalous crowd behaviour is a critical problem with the increase in human population. Anomalous events may include a person loitering about a place for unusual amounts of time; people running and causing panic; the size of a group of people growing over time etc. In this work, to detect...
We propose an algorithm that uses pressure image data to detect a person's sleeping posture and identifies different body limbs. Our algorithm can be used in monitoring bed-bound patients and assessing the risk of pressure ulceration. We used a GMM-based clustering approach for concurrent posture classification and limb identification. Our proposed technique, applied on 9 healthy subjects instructed...
There are large number of reports regarding bird and bat mortality due to strikes with turbine blades in wind farm applications. This issue is threatening the avian life especially migratory birds and bats. Avian monitoring techniques can be used to detect bird and bats, assess their activity, and make intelligent decision for construction of wind farms. In this paper, an IR monitoring approach is...
This paper proposes a clustering based image segmentation approach for elephant recognition. Appreciable recognition rate was achieved by k-means clustering technique followed by feature extraction and K nearest neighbour (K-NN) classifier. The k-means algorithm employs the concept of fitness and belongingness to provide a more adaptive andbetterclustering process as compared to several conventional...
In this paper we introduce a real-time obstacle detection and classification system designed to assist visually impaired people to navigate safely, in indoor and outdoor environments, by handling a smartphone device. We start by selecting a set of interest points extracted from an image grid and tracked using the multiscale Lucas - Kanade algorithm. Then, we estimate the camera and background motion...
In this paper, we present a strategy for the detection and tracking of dynamic objects exploiting monocular omnidirectional side cameras. The main novelty of the approach is the use of solely motion based (optical flow) extracted image features from omnidirectional side cameras to continuously track parallel moving vehicles using a novel clustering algorithm. Firstly, optical flow features are extracted...
This paper describes a target detection system on transport infrastructures, based on monocular vision, for applications in the framework of Intelligent Transportation Systems (ITS). Using structured elements of the image, a vanishing point extraction is proposed to obtain an automatic calibration of the camera, without any prior knowledge. This calibration provides an approximate size of the searched...
Interaction of avian with turbines has become an important public policy issue, so identification and quantification of avian at turbine sites is crucial.
We present a novel technique for localisation of scene elements through sparse stereovision, targeted at obstacle detection. Applications are autonomous driving or robotics. Given a sparse 3D map computed from low-cost features and with many matching errors, we present a technique that can achieve localisation in a real-time context of all potential obstacles in front of the camera pair. We use v-disparity...
Vehicle tracking is an important topic in computer vision. With the development of Intelligent Transportation System (ITS), research of vehicle tracking has been more and more active. Most traditional vehicle tracking algorithms are based on background model, which are easily affected by light and perspective transform, and have difficulty to solve occlusion and camera motion. The proposed vehicle...
In this paper we analyze large user photo collections from Flickr in order to select the most appropriate tags to describe a geographical area. We cluster photos based on their latitude and longitude and divide large areas into smaller clusters, which we will refer to as "geo-clusters". Geo-clusters have a fixed size and are able to overlap. They do not cover the entire area of interest,...
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