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We introduce SceneNet RGB-D, a dataset providing pixel-perfect ground truth for scene understanding problems such as semantic segmentation, instance segmentation, and object detection. It also provides perfect camera poses and depth data, allowing investigation into geometric computer vision problems such as optical flow, camera pose estimation, and 3D scene labelling tasks. Random sampling permits...
Due to the diversity of body movements and uncertainty of recording occasion, human action recognition is still a challenging task, especially in real world. This paper provides a new method of representing the video with mid-level vision representation which is extracted from the discriminative supervoxels. In the proposed method, the discriminative supervoxels we extracted through a learning phase...
Vocal fold kinematics and its interaction with aerodynamic characteristics play a primary role in acoustic sound production of the human voice. Investigating the temporal details of these kinematics using high-speed videoendoscopic imaging techniques has proven challenging in part due to the limitations of quantifying complex vocal fold vibratory behavior using only two spatial dimensions. Thus, we...
Motion segmentation relies on identifying coherent relationships between image pixels that are associated with motion vectors. However, perspective differences can often deteriorate the performance of conventional techniques. In this paper, we develop a motion segmentation scheme that utilizes the motion map of a single frame to identify motion representations based on motion vanishing points. Segmentation...
The octopus uses the arm-swimming behavior primarily for escape, defense, or foraging. This mode of locomotion is comprised of two strokes, with the arms opening slowly and closing rapidly, and generally results in considerable propulsive acceleration. In light of the recent development by our group of an octopus-like eight-arm underwater robot, we are interested to analyze the details of the biological...
This paper addresses the challenge of detecting and localizing a poorly textured known object, by initially estimating its complete 3D pose in a video sequence. Our solution relies on the 3D model of the object and synthetic views. The full pose estimation process is then based on foreground/background segmentation and on an efficient probabilistic edge-based matching and alignment procedure with...
Tracking trajectory of three-dimensional trees is a difficult problem in computer animation and virtual reality. It requires not only high sense of reality for the morphology of trees and tree moving, but also adequate real-time. In this paper, we present a simulation method based on video data driven. Firstly, split out the main branches and leaves of trees from video images by using hybrid method...
Object discovery and modeling have been widely studied in the computer vision and robotics communities. SLAM approaches that make use of objects and higher level features have also recently been proposed. Using higher level features provides several benefits: these can be more discriminative, which helps data association, and can serve to inform service robotic tasks that require higher level information,...
In the percutaneous needle procedures using ultrasound (US) imaging, the needle should be detected precisely to avoid damage to the tissue and to get the samples from the appropriate site. Excessive artifacts and low resolution of the US images make it difficult to detect the needle and its tip. It is possible to enhance the needle image using image processing; and this work proposes a novel needle...
In this paper, we tackle the problem of mapping multiple 3D rigid structures and estimating their motions from perspective views through a car-mounted camera. The proposed method complements conventional localization and mapping algorithms (such as Visual Odometry and SLAM) to estimate motions of other moving objects in addition to the vehicle's motion. We present a theoretical framework for robust...
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