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Obstacle detection and tracking is a fundamental task for several Advanced Driver Assistance Systems (ADAS) and self-driving cars. Several approaches have been presented in the literature in the last years and many of them are based on visual sensors. In this paper we propose an approach that uses only stereo cameras to detect and track obstacles and compute visual odometry to get the vehicle's ego-velocity...
Fully automated vehicles and mobile robots operate in a shared environment with pedestrians. To minimize the risk for pedestrians, it is very important to track them in a precise way. As cameras are often installed in surveillance situations, they are used for tracking pedestrians in a shared environment. To improve the accuracy of the tracking, it is necessary to include all available context information...
In most of the scenarios, accidents occur due to the carelessness of the driver. To reduce the accidents sharing of the vehicle's dynamics information is essential. The primary vehicle uses several sensors to collect information which were transmitted to the next subordinate vehicles that follow it. For communicating huge data between vehicles we need a Multiple Input Multiple Output Radio Frequency...
In order to track the localizations of mobile devices in an unknown environment, this paper presents an architecture combining a monocular camera and an inertial measurement unit (IMU) in ubiquitous mobile devices. The IMU module provides acceleration and angular velocity with high-frequency, but the IMU-based motion tracking is more inclined to collapse due to the drift integration. While the vision-based...
As the problem of traffic congestion is increasing day by day, there is a pressing need for the introduction of advanced system to monitor and control traffic efficiently. The analysis of traffic data collected from the camera based systems are the main method used for this purpose. The method presented here can detect vehicles, track and count them with high accuracy on videos from the intersection...
This study demonstrates computational methods for the automatic detection and tracking of fish from video sequences. The research in this subject is very important especially in fish farming companies and for nature protection around the world. The process of automated control and counting of individual species of fish has a supportive contribution both in the nature conservation and in the food industry...
In video surveillance to count the number of people walking through a corridor or door people counting is used. Counting persons passing through supervised area is important issue of this domain. System of people counting is important for security application (such as in the situation of an evacuation, it is vital to know how many people are present inside the surveillance area at any given time),...
In this paper, we propose a method to improve ego-motion estimation. In the proposed method, feature points from input binocular stereo image pairs are detected using the Speeded Up Robust Features method and descriptor vectors are generated for the features. Semi-Global Matching is then performed to ensure the quality and quantity of the matching features, which are used in conjunctions with camera...
An automated physiotherapy exercise monitoring system requires good postural structure and pose information. Most of human movements for daily activity pivoted on lower limb that requires intensive care, especially for the stroke patient. However, there are a lot of uncertainties in human stance, movement and strength that need to be observed for good rehabilitation training. Hence, home-based rehabilitation...
IP Pan-Tilt-Zoom cameras (IP PTZ) are now common in videosurveillance areas as they are easy to deploy and can take high resolution pictures of targets in a large field of view thanks to their pan-tilt and zoom capabilities. However the closer the view is, the higher is the risk to lose your target. Furthermore, off-the-shelf cameras used in large videosurveillance areas present important motion delays...
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...
Tracking can be defined as the problem of estimating the trajectory of an object in image sequence as it moves around a scene. In other words, a tracker assigns consistent labels to the tracked objects in different frames of a video. One of the most widely used technique to this task is the Kalman filter. This paper presents a car tracker using Kalman filter and optical flow, which shows excellent...
The past few years have shown the growth in three-dimensional (3D) content and stereoscopic 3D displays. These displays aim to provide realism through an illusion of depth to the viewers. However, stereoscopic 3D displays are only prevalent as larger format displays like television sets and cinemas because of specialized hardware requirements. This research provides a method for users to perceive...
This work proposes a fusion of inertial measurement units (IMUs) and a visual tracking system on an embedded device. The sensor-to-sensor calibration and the pose estimation are both achieved through an unscented Kalman filter (UKF). Two approaches for a UKF-based pose estimation are presented: The first uses the estimated pose of the visual SLAM system as measurement input for the UKF; The second...
A non-contact method to extract human cardiac pulse rate non-invasively is more affordable and convenient compared with conventional method using contact electrode. This paper developed a video method to extract pulse rate based on smartphone. Using the front camera of smartphone to capture image frame data of human face region, defined as ROI (region of interest) for extracting PPG signal. And to...
In this paper, we describe a novel design for a real-time localization system capable of tracking a highly maneuverable target within a 360 degree range of the camera. The target is defined for surveillance. The approach to tracking includes using a controllable camera which is re-oriented according to the tracked location of the target object. Fuzzy logic is used to determine the direction of motion...
In this paper, a novel method for people detection and tracking is proposed, based on stereo vision. Each person is represented by a group of the feature points. In this method feature point extraction and 2D space construction of projected points on the ground plane is performed in order to provide top view. Occlusion, as a main challenge in tracking systems, can be addressed by top view scene. A...
In this paper, we present a vision based tracking scheme to capture kinematic data of two laparoscopic tools in a surgical trainer or simulator. Camshift algorithm along with Kalman filter is used for occlusion-free tracking of multiple markers attached to the tools. Tracking of the markers in 3D is achieved, using a single stationary camera, by tracking variations in the size of the markers in the...
Nowadays, many lectures and presentations are recorded and broadcasted for teleteaching applications. When no human camera crew is present, the most obvious choice is for static cameras. In order to enhance the viewing experience, more advanced systems automatically track and steer the camera towards the lecturer. In this paper we propose an even more advanced system that tracks the lecturer while...
Human tracking is a comprehensive framework for tracking coarse human model performed from sequences of synchronized monocular grayscale images in single or multiple camera system coordinates. It is nothing but segmenting an interested human from video scene and keep track if it continuously. It demonstrates the feasibility of an end to end person tracking system where initially it start background...
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