Recent years have seen remarkable progress in semantic segmentation. Yet, it remains a challenging task to apply segmentation techniques to video-based applications. Specifically, the high throughput of video streams, the sheer cost of running fully convolutional networks, together with the low-latency requirements in many real-world applications, e.g. autonomous driving, present a significant ...

Video segmentation is different from segmentation of a single image. While several correct solutions may exist for segmenting a single image, there needs to be a consistency among segmentations of each frame for video segmentation. Previous approaches of video segmentation concentrate on motion, or combine motion and color information in a batch fashion. We propose a maximum a posteriori probab...

Object segmentation and tracking are important techniques in video applications. In this paper, we present a novel system for active contour tracking of moving objects in video sequences. Our method includes preprocessing to identify an initial object contour, and object contour segmentation to refine the contour of the moving object. The edge flows and ant colony optimization are incorporated ...

Object segmentation from a video stream is an essential task in video processing and forms the foundation of scene understanding, object-based video encoding (e.g. MPEG4), various surveillance and 2D to pseudo 3D conversion applications. The task is difficult and exacerbated by the advances in video capture and storage (e.g. HDTV, QuadHDTV). Increased resolution of the sequences requires develo...

In recent years, with the amount of video data increasing rapidly, automatic methods are needed to deal with large-scale video data sets in various applications. A common and fundamental preprocess for these applications is video segmentation. Based on the segmentation results, video has a hierarchical representation structure of frames, shots, and scenes from the low level to high level. And f...

Mean shift is a nonparametric estimator of density which has been applied to image and video segmentation. Traditional mean shift based segmentation uses a radially symmetric kernel to estimate local density, which is not optimal in view of the often structured nature of image and more particularly video data. In this paper we present an anisotropic kernel mean shift in which the shape, scale, ...

Hyperlinked video is video in which speciic objects are made selectable by some form of user interface, and the user's interactions with these objects modify the presentation of the video. Identifying and tracking the objects remains one of the chief diiculties in authoring hyperlinked video; we solve this problem through the use of a video tracking and segmentation algorithm that uses color, t...

Abstract Can our video understanding systems perceive objects when a heavy occlusion exists in scene? To answer this question, we collect large-scale dataset called OVIS for occluded instance segmentation, that is, to simultaneously detect, segment, and track instances scenes. consists of 296k high-quality masks from 25 semantic categories, where object occlusions usually occur. While human vis...