In this paper a novel connectionist approach for video compression is presented. The basic idea is to extend to the temporal dimension the architecture used for the compression of still images. A multilayer perceptron (MLP) with in nite impulse response (IIR) synapses, embedded in a new quad-tree framework for video segmentation, is employed to take into account the video temporal dynamics. In ...

We present an efficient video segmentation and tracking strategy based on edge information to assist object-based video coding, motion estimation, and motion compensation for MPEG-4 and MPEG-7. The proposed algorithm utilizes the human visual perception to provide edge information. Three parameters are introduced and described based on edge information from the analysis of a local histogram. An...

Dynamic analysis of video sequences often relies on the segmentation of the sequence into regions of consistent motions. Approaching this problem requires a definition of which motions are regarded as consistent. Common approaches to motion segmentation usually group together points or image regions that have the same motion between successive frames (where the same motion can be 2D, 3D, or non...

In this paper, we introduce TIVE, a Toolbox for Identifying Video instance segmentation Errors. By directly operating output prediction files, TIVE defines isolated error types and weights each type’s damage to mAP, the purpose of distinguishing model characters. decomposing localization quality in spatial–temporal dimensions, model’s potential drawbacks on spatial temporal association can be r...

In unsupervised video object segmentation (UVOS), the whole might segment wrong target due to lack of initial prior information. Also, in semi-supervised (SVOS), frame with a fine-grained pixel-level mask is essential good accuracy. It expensive and laborious provide accurate masks for each training sequence. To address this issue, We present weak user interactive UVOS approach guided by simple...

Interactive video segmentation has become a popular topic in computer vision and computer graphics. Discrete optimization using maximum ow algorithms is one of the preferred techniques to perform interactive video segmentation. This paper extends pixel based graph cut approaches to overcome the problem of high memory requirements. The basic idea is to use a graph cut optimization framework on t...

We address a variety of challenges for analysis and enhancement of Computational Video. We present novel post-processing methods to bridge the difference between professional and casually shot videos mostly seen on online sites. Our research presents solutions to three well-defined problems: (1) Video stabilization and rolling shutter removal in casually-shot, uncalibrated videos; (2) Content-a...