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Classification of human actions is very challenging and important in many video-based applications. Two common features, i.e., the hand-crafted and the deep-learned ones are usually adopted for video representation and have been proven to be effective in many famous datasets in the literature. However, the hand-crafted feature lacks the ability to detect the discriminative and semantic features and...
Drones equipped with cameras are emerging as a powerful tool for large-scale aerial 3D scanning, but existing automatic flight planners do not exploit all available information about the scene, and can therefore produce inaccurate and incomplete 3D models. We present an automatic method to generate drone trajectories, such that the imagery acquired during the flight will later produce a high-fidelity...
Due to the iteration-varying initial position, it is complicated in path-tracking for the mobile service robot. Perspective dynamic system (PDS) provides a theory to formulate the system, which transmits from the apparent motion to the image plane and provides a good control theoretic framework to estimate motion problem. The proposed iterative learning control (ILC) algorithms not only consider errors...
The exponentially increasing use of moving platforms for video capture introduces the urgent need to develop the general background subtraction algorithms with the capability to deal with the moving background. In this paper, we propose a multilayer-based framework for online background subtraction for videos captured by moving cameras. Unlike the previous treatments of the problem, the proposed method...
Progress in Multiple Object Tracking (MOT) has been historically limited by the size of the available datasets. We present an efficient framework to annotate trajectories and use it to produce a MOT dataset of unprecedented size. In our novel path supervision the annotator loosely follows the object with the cursor while watching the video, providing a path annotation for each object in the sequence...
This paper incorporates sampling-based global path planning with model predictive image-based visual servoing (IBVS) for quadrotor unmanned aerial vehicles (UAVs) equipped with a fixed camera. The proposed method produces safe control inputs of quadrotor in obstacle environment by taking image feature kinematics into account. Firstly, we utilize a sampling-based algorithm for optimal path planning,...
This paper considers the multi-camera motion segmentation problem using unsynchronized videos: given two video clips containing several moving objects, captured by unregistered, unsynchronized cameras with different viewpoints, our goal is to assign features to moving objects in the scene. This problem challenges existing methods, due to the lack of registration information and correspondences across...
In recent years average life expectancy in developed countries has increased, hence the amount of people which depend on a wheeled walking frame and in addition are visually handicapped has grown. The independent mobility of this people is often limited since they need guidance by other humans. Recent research focused on technical guidance systems implemented on a walking frame. The mobile vehicle...
The ability to identify, follow, approach, and intercept a non-stationary target is a desirable capability of autonomous micro aerial vehicles (MAV) and puts high demands on reliable target perception, fast trajectory planning, and stable control. We present a fully autonomous MAV that lands on a planar platform mounted on a ground vehicle, relying only on onboard sensing and computing. We evaluate...
In this paper we propose an effective vision-based navigation method that allows a multirotor vehicle to simultaneously reach a desired goal pose in the environment while constantly facing a target object or landmark. Standard techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast maneuvers) do not...
We propose a visual SLAM (Simultaneous Localization And Mapping) system able to perform robustly in populated environments. The image stream from a moving RGB-D camera is the only input to the system. The computed map in real-time is composed of two layers: 1) The unpopulated geometrical layer, which describes the geometry of the bare scene as an occupancy grid where pieces of information corresponding...
Intelligent Intersection Traffic Management has become increasingly important because of the need to reduce congestion and improve the overall travel experience of commuters. Given the dynamic nature of everyday city traffic, this paper proposes real-time processing of videos from cameras to estimate the traffic density and optimize the signal parameters of the intersection. The region-of-interest...
Plant health is an essential factor to reduce the number of import in a country. In this research, we use paddy as an example to understand plant health. Our research is motivated by our belief that technology might aid in reducing chances of failed paddy harvest in Indonesia. To understand the plant health of paddy, we designed unmanned aerial vehicle (UAV) integrated pocket cameras to record near...
This paper presents a stochastic optimal control approach suitable for implementation on small unmanned aerial vehicles (UAV). The controller provides tracking of a target at a desired distance, keeps the target away from the sector of blind spots and prevents flying over the target to avoid the flipping images in the camera's recorded sequence. The controller is based on a two-dimensional stochastic...
For the understanding of the dynamics inside crowds reliable empirical data are needed. On that basis the safety and comfort for pedestrians can be increased and models reflecting the real dynamics can be designed. For that purpose we are developing the free framework PeTrack collecting data from laboratory experiments. With the new integration of the detection of individual codes the presented framework...
Detection of falling is an important research issue to develop smart healthcare technologies for elderly people as the population is rapidly increasing. To achieve the goal, accurate human tracking is imperative to detect a fall regardless of distance and occlusions. However, existing technologies are focusing on either 2D tracking with a single camera or 3D tracking using a depth camera (distance...
The analysis of multimodal data collected by innovative imaging sensors, Internet of Things (IoT) devices and user interactions, can provide smart and automatic distant monitoring of patients and reveal valuable insights for early detection and/or prevention of events related to their health situation. In this paper, we present a platform called ICT4LIFE which starting from low-level data capturing...
Appearance based multi-object tracking (MOT) is a challenging task, specially in complex scenes where objects have similar appearance or are occluded by background or other objects. Such factors motivate researchers to propose effective trackers which should satisfy real-time processing and object trajectory recovery criteria. In order to handle both mentioned requirements, we propose a robust online...
Moving objects pose a challenge to every video stabilization algorithm. We present a novel, efficient filtering technique that manages to remove outlier motion vectors caused from moving objects in a per-pixel smoothing setting. We leverage semantic information to change the calculation of optical flow, forcing the outliers to reside in the edges of our semantic mask. After a ‘content-preserving warping’...
Guided bombs use different sensors as an input to correct its trajectory to a desired target. Some of them use optical sensors to compute the relative state between the guided system and the target. These systems usually use bang-off-bang controllers to align the line of sight towards the target, producing a quasi-straight path and a fixed attitude angle. The present work proposes an extension of...
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