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Ultra low delay video transmission is becoming increasingly important. Video-based applications with ultra low delay requirements range from teleoperation scenarios such as controlling drones or telesurgery to autonomous control of dynamic processes using computer vision algorithms applied on real-time video. To evaluate the performance of the video transmission chain in such systems, it is important...
This paper provides a novel summarization method for driving data, including a driving video captured by car-mounted camera, vehicle behavior such as velocity, steering angle, and other information. While a large amount of the driving data have been gathered recently, looking back method, however, has not been well-considered. In this paper, we integrate various information from the driving data as...
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,...
3D reconstruction is one of the long lasting research topics in computer vision. It is the task of regenerating a model in three-dimensional (3D) space by images taken from the scene. An image-based method for 3D reconstruction based on intersection of planar visual hulls from projective images taken by multiview videos is proposed. Reconstruction can be performed without any further information related...
This paper proposes a simple spatial feature combined with temporal characteristics to classify human interactions from surveillance cameras, which are far from the action scene. For the first stage, data is collected from a horizontal view. Then, the history of distance between two persons is stored during time as a temporal feature called distance signature. We use Spatio-Temporal Interest Points...
In this paper we propose an interactive method for the segmentation of objects in video. We aim to exploit multiple modalities to reduce the dependency on color discrimination alone. Given an initial segmentation for the first and last frame of a video sequence, we aim to propagate the segmentation to the intermediate frames of the sequence. Video frames are first segmented into superpixels. The segmentation...
Important issues such as low image quality and human operators' reactivity can seriously reduce the effectiveness of video surveillance systems. Digital video surveillance is used in conjunction with video analytics, which is the semantic analysis of video data through signal and image processing techniques. This paper presents a novel algorithm for real time detection of abandoned and removed objects,...
This paper presents a novel method for accurate motion detection in dynamic scenes without any prior information about moving object or dynamic scenes. Moving object detection is mainly performed by segmentation of estimated optical flow field, which is calculated by classical Horn Schunck algorithm. Robust ego-motion estimation is performed prior to the optical flow segmentation, which largely decreases...
This paper presents a novel approach to stabilize video sequences based on low-rank matrix decomposition. Compared to previous methods which are based on simplified models, our stabilization system can work in situations where significant depth variations exist in the scenes and the camera undergoes large translational movement. We formulate the stabilized frames as a low-rank matrix. This allows...
We present a method for reconstruction of the visual hull (VH) of an object in real-time from multiple video streams. A state of the art polyhedral reconstruction algorithm is accelerated by implementing it for parallel execution on a multi-core graphics processor (GPU). The time taken to reconstruct the VH is measured for both the accelerated and non-accelerated implementations of the algorithm,...
We propose here to acquire high resolution sequences of a person's face using a pan-tilt-zoom (PTZ) network camera. This capability should prove helpful in forensic analysis of video sequences as frames containing faces are tagged, and within a frame, windows containing faces can be retrieved. The system starts in pedestrian detector mode, where the lens angle is set widest, and detects people using...
In this paper, an information acquisition system based on a kind of attitude sensor is presented, which can analyze the technique characteristics of freestyle skiing aerials. The system consists of four modules and can acquire the kinematical parameters such as acceleration, angular velocity in time; also we can get other parameters through designed algorithms such as velocity, angular acceleration...
We present a method for improving human segmentation results in calibrated, multi-view environments using features derived from both pixel (image) and voxel (volume) space. The main focus of this work is to develop a low-cost, vision-based system for passive activity monitoring of older adults in the home, to capture early signs of illness and functional decline and allow seniors to live independently...
A novel model of fuzzy clustering neural network is discussed, which synthesizes unsupervised fuzzy competitive learning algorithm and self-organized competitive network. Based on this model, an algorithm of abrupt video shot boundary detection is presented which is a two-stage clustering on a linear feature space. The experimental results obtained demonstrate that the algorithm is feasible and efficient.
This demonstration presents a social interaction analysis system designed to operate in real-time and under real environment conditions. A webcam is used to capture videos of a group of people interacting in an unconstrained environment. Locations of multiple people and their head poses are extracted from the videos. Direct pairwise interactions are detected based on the relative distance and head...
Blind people navigate safely through a familiar room based on strong expectations about the location of objects. If something has been moved, added or removed, it can present a difficulty and potentially a danger. Human eyes are one of the most important body parts that help humans to understand and interact with their surroundings. Most learning and recognition of objects around us is accomplished...
In this paper, a motion and similarity-based fake detection algorithm is presented for biometric face recognition systems. First, an input video is segmented as foreground and background regions. Second, the similarity is measured between a background region, i.e., a region without a face and upper body, and an original background region recorded at an initializing stage. Third, a background motion...
This paper presents a new video stabilization algorithm for digital video cameras. The proposed technique directly estimates correction motion through point-feature trajectories, so that our method can be free from the error accumulation as time goes on. Furthermore, an adaptive RANSAC is proposed to estimate a robust correction motion. Experimental results show that the proposed algorithm can robustly...
We address the problem of searching camera network videos to retrieve frames containing specified individuals. We show the benefit of utilizing a learned probabilistic model that captures dependencies among the cameras. In addition, we develop an active inference framework that can request human input at inference time, directing human attention to the portions of the videos whose correct annotation...
In this paper, we address the problem of vehicle detection and tracking with low-angle cameras by combining windshield detection and feature points clustering, effectively fusing several primitive image features such as color, edge and interest point. By exploring various heterogenous features and multiple vehicle models, we achieve at least two improvements over the existing methods: higher detection...
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