The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Omnidirectional, also referred to as 360º, visual content provides an immersive experience since it allows users to view a visual scene from different directions. The overall content typically covers a full sphere, and omnidirectional videos or images are processed to obtain a projection on a 2D plane of a fraction of the sphere (aka viewport), which is shown to the user. Therefore, users can look...
The task of object tracking in rectangular videos has been addressed in recent years by many researchers, where each method tries to propose a solution for a special challenge. Handling a variety of challenging situation of object tracking in 360-degree videos is still an unsolved problem and needs to be more considered. In the real world, the challenging situations include moving camera, high-resolution...
This paper deals with automatic estimation of the horizon in videos from fixed surveillance cameras. The proposed algorithm is fully automatic in the sense that no user input is needed per-camera and it works with various scenes (indoor, outdoor, traffic, pedestrian, livestock, etc.). The algorithm detects moving objects, tracks them in time, assesses some of their geometric properties related to...
Viewpoint variation is a major challenge in video- based human action recognition. We exploit the simultaneous RGB and Depth sensing of RGB-D cameras to address this problem. Our technique capitalizes on the complementary spatio-temporal information in RGB and Depth frames of the RGB-D videos to achieve viewpoint invariant action recognition. We extract view invariant features from the dense trajectories...
Depth sensors open up possibilities of dealing with the human action recognition problem by providing 3D human skeleton data and depth images of the scene. Analysis of human actions based on 3D skeleton data has become popular recently, due to its robustness and view-invariant representation. However, the skeleton alone is insufficient to distinguish actions which involve human-object interactions...
Existing counting methods often adopt regression-based approaches and cannot precisely localize the target objects, which hinders the further analysis (e.g., high-level understanding and fine-grained classification). In addition, most of prior work mainly focus on counting objects in static environments with fixed cameras. Motivated by the advent of unmanned flying vehicles (i.e., drones), we are...
Gesture is a natural interface in interacting with wearable devices such as VR/AR helmet and glasses. The main challenge of gesture recognition in egocentric vision arises from the global camera motion caused by the spontaneous head movement of the device wearer. In this paper, we address the problem by a novel recurrent 3D convolutional neural network for end-to-end learning. We specially design...
Hand gestures provide a natural and an intuitive way of user interaction in AR/VR applications. However, the most popular and commercially available devices such as the Google Cardboard and Wearality1 still employ only primitive modes of interaction such as the magnetic trigger, conductive lever and have limited user-input capability. The truly instinctual gestures work only with inordinately priced...
Accurately tracking the six degree-of-freedom pose of an object in real scenes is an important task in computer vision and augmented reality with numerous applications. Although a variety of algorithms for this task have been proposed, it remains difficult to evaluate existing methods in the literature as oftentimes different sequences are used and no large benchmark datasets close to realworld scenarios...
The feeling of presence in virtual reality has enabled a large number of applications. These applications typically deal with 360° content. However, a large amount of existing content is available in terms of images and videos i.e 2D content. Unfortunately, these do not react to the viewer's position or motion when viewed through a VR HMD. Thus in this work, we propose reactive displays for VR which...
The speed characteristic of moving contact is vital to the high voltage circuit breakers. But due to the contacts of high voltage circuit breaker are completely isolated by arc chamber, the common measurement methods have some disadvantages. In this paper, a new method for measuring the speed characteristics based on machine vision algorithm is developed. This noninvasive method just needs to draw...
This paper addresses the problem of jointly recognizing object fluents and tasks in egocentric videos. Fluents are the changeable attributes of objects. Tasks are goal-oriented human activities which interact with objects and aim to change some attributes of the objects. The process of executing a task is a process to change the object fluents over time. We propose a hierarchical model to represent...
This paper presents an extension of block-based motion estimation for omnidirectional videos, based on a translational object motion model that accounts for the spherical geometry of the imaging system. We use this model to design a new algorithm to perform block matching in sequences of panoramic frames that are the result of the equirectangular projection. Experimental results demonstrate that significant...
First-person videos (FPVs) captured by wearable cameras have undesired shakiness because of fast changing views. When existing video stabilization techniques are applied, FPVs are transformed into cinematographic videos, losing the First-person motion information (FPMI) such as the recorder's interests and actions. We propose a system that can enhance viewability of FPVs by stabilizing them while...
This paper proposes a moving object detection algorithm which can handle videos taken by a moving camera in the presence of pronounced parallax. The paper considers the idea that objects in a image can be considered to be spatially distributed across multiple planes, the movement of each of which can be estimated using a Visual Odometry (VO) algorithm. For each plane, a Homography matrix between consecutive...
We introduce a novel formulation of temporal color constancy which considers multiple frames preceding the frame for which illumination is estimated. We propose an end-to-end trainable recurrent color constancy network – the RCC-Net – which exploits convolutional LSTMs and a simulated sequence to learn compositional representations in space and time. We use a standard single frame color constancy...
In this paper, we develop deep spatio-temporal neural networks to sequentially count vehicles from low quality videos captured by city cameras (citycams). Citycam videos have low resolution, low frame rate, high occlusion and large perspective, making most existing methods lose their efficacy. To overcome limitations of existing methods and incorporate the temporal information of traffic video, we...
Detecting logo frequency and duration in sports videos provides sponsors an effective way to evaluate their advertising efforts. However, general-purposed object detection methods cannot address all the challenges in sports videos. In this paper, we propose a mutual-enhanced approach that can improve the detection of a logo through the information obtained from other simultaneously occurred logos...
Anticipating human intention by observing one’s actions has many applications. For instance, picking up a cellphone, then a charger (actions) implies that one wants to charge the cellphone (intention) (Fig. 1). By anticipating the intention, an intelligent system can guide the user to the closest power outlet. We propose an on-wrist motion triggered sensing system for anticipating daily intentions,...
To watch 360° videos on normal 2D displays, we need to project the selected part of the 360° image onto the 2D display plane. In this paper, we propose a fully-automated framework for generating content-aware 2D normal-view perspective videos from 360° videos. Especially, we focus on the projection step preserving important image contents and reducing image distortion. Basically, our projection method...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.