21 papers · ranked by Valyu relevance
Zhigao Cui, Ke Jiang, Tao Wang
Moving object segmentation is the most fundamental task for many vision-based applications. In the past decade, it has been performed on the stationary camera, or moving camera, respectively. In this paper, we show that the moving object segmentation can be addressed in a unified framework for both type of cameras. The…
Geethu Miriam Jacob, Sukhendu Das
Moving Object Segmentation is a challenging task for jittery/wobbly videos. For jittery videos, the non-smooth camera motion makes discrimination between foreground objects and background layers hard to solve. While most recent works for moving video object segmentation fail in this scenario, our method generates an…
Pia Bideau, Erik Learned-Miller
Motion segmentation is currently an active area of research in computer Vision. The task of comparing different methods of motion segmentation is complicated by the fact that researchers may use subtly different definitions of the problem. Questions such as "Which objects are moving?", "What is background?", and "How…
Cornelia Beck, Thilo Ognibeni, Heiko Neumann, Ernest Greene
Occlusions–A Biologically Inspired Model Motion Based Segmentation Authors: ['Cornelia Beck' 'Thilo Ognibeni' 'Heiko Neumann' 'Ernest Greene'] Background Optic flow is an important cue for object detection. Humans are able to perceive objects in a scene using only kinetic boundaries, and can perform the task even when…
Tao Zhuo, Zhiyong Cheng, Peng Zhang, Yongkang Wong + 1 more
'Mohan Kankanhalli'] Abstract—Unsupervised video object segmentation aims to automatically segment moving objects over an unconstrained video without any user annotation. So far, only few unsupervised online methods have been reported in literature and their performance is still far from satisfactory, because the…
Dehao Qin, Ripon K. Saha, Suren Jayasuriya, Jinwei Ye + 1 more
Moving object segmentation in the presence of atmospheric turbulence is highly challenging due to turbulence-induced irregular and time-varying distortions. In this paper, we present an unsupervised approach for segmenting moving objects in videos downgraded by atmospheric turbulence. Our key approach is a…
Carlos Cuevas, Eva María Yáñez, Narciso García, Vittorio M.N. Passaro
'Vittorio M.N. Passaro'] An advanced and user-friendly tool for fast labeling of moving objects captured with surveillance sensors is proposed, which is available to the public. This tool allows the creation of three kinds of labels: moving objects, shadows and occlusions. These labels are created at both the pixel…
Samuele Virgili, Thomas Buffet, Matthew Chalk, Olivier Marre
The center surround structure of ganglion cells receptive fields is suited for edge detection, a first step towards image segmentation. However, in a dynamical visual scene with moving objects, it is less clear how the retina represents the boundaries of moving objects and therefore contributes to motion segmentation.…
Steven Wiesner, Bikalpa Ghimire, Xin Huang
Segregating objects from one another and the background is essential for scene understanding, object recognition, and visually guided action. In natural scenes, it is common to encounter spatially separated stimuli, such as distinct figure-ground regions, adjacent objects, and partial occlusions. Neurons in mid- and…
A. F. M. Saifuddin Saif, Anton Satria Prabuwono, Zainal Rasyid Mahayuddin
'Zainal Rasyid Mahayuddin'] Motion analysis based moving object detection from UAV aerial image is still an unsolved issue due to inconsideration of proper motion estimation. Existing moving object detection approaches from UAV aerial images did not deal with motion based pixel intensity measurement to detect moving…
Rui Yao, Guosheng Lin, Shixiong Xia, Jiaqi Zhao + 1 more
Object segmentation and object tracking are fundamental research area in the computer vision community. These two topics are dicult to handle some common challenges, such as occlusion, deformation, motion blur, and scale variation. The former contains heterogeneous object, interacting object, edge ambiguity, and shape…
Dong Lao, Ganesh Sundaramoorthi
We present a general framework and method for simultaneous detection and segmentation of an object in a video that moves (or comes into view of the camera) at some unknown time in the video. The method is an online approach based on motion segmentation, and it operates under dynamic backgrounds caused by a moving…
Matthias Brucklacher, Giovanni Pezzulo, Francesco Mannella, Gaspare Galati + 1 more
Efficient sensory detection requires the capacity to ignore task-irrelevant information, for example when optic flow patterns created by egomotion need to be disentangled from object perception. To investigate how this is achieved in the visual system, predictive coding with sensorimotor mismatch detection is an…
Wenguang Yang, Kan Ren, Minjie Wan, Xiaofang Kong + 2 more
'Christian Haubelt'] This article primarily focuses on the localization and extraction of multiple moving objects in images taken from a moving camera platform, such as image sequences captured by drones. The positions of moving objects in the images are influenced by both the camera’s motion and the movement of the…
Xin Huang, Bikalpa Ghimire, Anjani Sreeprada Chakrala, Steven Wiesner
Motion speed provides a salient cue for visual segmentation, yet how the visual system represents and differentiates multiple speeds remains poorly understood. Here, we investigated the neural coding of multiple speeds. First, we characterized the perceptual capacity of human and macaque subjects to segment overlapping…
Anh Vu Le, Seung-Won Jung, Chee Sun Won
Moving objects of interest (MOOIs) in surveillance videos are detected and encapsulated by bounding boxes. Since moving objects are defined by temporal activities through the consecutive video frames, it is necessary to examine a group of frames (GoF) to detect the moving objects. To do that, the traces of moving…
Katharina Löffler, Tim Scherr, Ralf Mikut
Automatic cell segmentation and tracking enables to gain quantitative insights into the processes driving cell migration. To investigate new data with minimal manual effort, cell tracking algorithms should be easy to apply and reduce manual curation time by providing automatic correction of segmentation errors. Current…
Young Hwan Chang, Jeremy Linsley, Josh Lamstein, Jaslin Kalra + 7 more
Live-cell imaging is an important technique to study cell migration and proliferation as well as image-based profiling of drug perturbations over time. To gain biological insights from live-cell imaging data, it is necessary to identify individual cells, follow them over time and extract quantitative information.…
Rama El-khawaldeh, Mason Guy, Finn Bork, Nina Taherimakhsousi + 6 more
This work presents a generalizable computer vision (CV) and machine learning model that is used for automated real-time monitoring and control of a diverse array of workup processes. Our system simultaneously monitors multiple physical parameters (e.g., liquid level, homogeneity, turbidity, solid, residue, and color)…
Alexander E. Siemenn, Eunice Aissi, Fang Sheng, Armi Tiihonen + 3 more
In materials research, the task of characterizing hundreds of different materials traditionally requires equally many human hours spent measuring samples one by one. We demonstrate that with the integration of computer vision into this material research workflow, many of these tasks can be automated, significantly…
Authors not listed
The exponential growth of chemical literature necessitates the development of automated tools for extracting and curating molecular information from unstructured scientific publications into open-access chemical databases. Current optical chemical structure recognition (OCSR) and named entity recognition solutions…