We present the first comprehensive video polyp segmentation (VPS) study in deep learning era. Over years, developments VPS are not moving forward with ease due to lack of large-scale fine-grained annotations. To address this issue, we introduce a high-quality frame-by-frame annotated dataset, named SUN-SEG, which contains 158,690 colonoscopy frames from well-known SUN-database. provide addition...

A common approach to analysis of mouse behavior recorder by video tracking systems employs manual segmentation and labeling of mouse activity into behavioral acts. Developed automatic methods allow segmentation only to lingering and progression segments, suffer from poor precision and require parameter tuning. We propose a novel approach based on hidden Markov model for simultaneous segmentatio...

Previous video matting approaches mostly adopt the “binary segmentation + matting” strategy, i.e., first segment each frame into foreground and background regions, then extract the fine details of the foreground boundary using matting techniques. This framework has several limitations due to the fact that binary segmentation is employed. In this paper, we propose a new supervised video matting ...

The article presents the concept of real-time implementation computing tasks in video surveillance systems. A pipeline implementation of a multimodal background generation algorithm for colour video stream and a moving objects segmentation based on brightness, colour and textural information in reconfigurable resources of FPGA device is described. System architecture, resource usage and segment...

This paper addresses the implementation of the Region Competition algorithm for segmenting stereoscopic video sequences. The segmentation performed by this algorithm is an essential stage for the 3D characterization of artificial muscles. Image sequences are acquired by a two-cam computer vision system. The aim of this work is to come up with optimal and efficient segmentation of these images; ...

We in this paper solve the problem of high-quality automatic real-time background cut for 720p portrait videos. We first handle the background ambiguity issue in semantic segmentation by proposing a global background attenuation model. A spatial-temporal refinement network is developed to further refine the segmentation errors in each frame and ensure temporal coherence in the segmentation map....

Automatic video segmentation and action recognition has been a long-standing problem in computer vision. Much work in the literature treats video segmentation and action recognition as two independent problems; while segmentation is often done without a temporal model of the activity, action recognition is usually performed on pre-segmented clips. In this paper we propose a novel method that av...

The increased availability and usage of multimedia information have created a critical need for efficient multimedia processing algorithms. These algorithms must offer capabilities related to browsing, indexing, and retrieval of relevant data. A crucial step in multimedia processing is that of reliable video segmentation into visually coherent video shots through scene change detection. Video s...

Dynamic video segmentation is an important research topic in computer vision. In this paper, we present a novel recursive Kernel Density Learning framework based video segmentation method. In the algorithm, local maximum in the density functions is approximated recursively via a mean shift method firstly. Via a proposed thresholding scheme, components and parameters in the mixture Gaussian dist...

We present an approach to semi-supervised video object segmentation, in the context of the DAVIS 2017 [8] challenge. Our approach combines category-based object detection, category-independent object appearance segmentation and temporal object tracking. We are motivated by the fact that the objects semantic category tends not to change throughout the video while its appearance and location can ...