We present in this paper an intelligent video data visualization tool, based on semantic classification, for retrieving and exploring a large scale corpus of videos. Our work is based on semantic classification resulting from semantic analysis of video. The obtained classes will be projected in the visualization space. The graph is represented by nodes and edges, the nodes are the keyframes of ...

The widespread deployment of end-to-end encryption protocols such as HTTPS and QUIC has reduced the visibility for operators into traffic on their networks. Network operators need the visibility to monitor and mitigate Quality of Experience (QoE) impairments in popular applications such as video streaming. To address this problem, we propose a machine learning based approach to monitor QoE metr...

This paper defines a system for automatic analysis of, and highlights extraction from football television footage. The analysis is based solely on visual or cinematic information in the video, using shot type classification and colour analysis on video frames. Two different versions of the system have been developed, enabling work on decoded video frames as well as direct analysis of the compre...

− − − −− − − −A video encoder has to make many mode decisions in order to achieve the goal of a low bit rate, high quality, and fast implementation. We propose a general classification based approach to making such mode decisions accurately and efficiently. We first illustrate the approach using the Intra-Inter coding mode decision. We then focus on the decision to skip or code a frame for rate...

This proposed research work describes a system that is used for recognition and classification of vehicles from low vision video footage captured by surveillance cameras. It's an important step for many applications in intelligent transportation systems and video surveillance. For carrying out the above said process, first step is detection of the vehicles present in the enhanced video frame & ...

In this work we investigate a weakly-supervised approach to learning facial attributes of humans in video. Given a small set of images labeled with attributes and a much larger unlabeled set of video tracks, we train a classifier to recognize these attributes in video data. We make two contributions. First, we show that training on video data improves classification performance over training on...

A video encoder has to make many mode decisions in order to achieve the goal of a low bit rate, high quality, and fast implementation. We propose a general classification based approach to making such mode decisions accurately and efficiently. We first illustrate the approach using the Intra-Inter coding mode decision. We then focus on the decision to skip or code a frame for rate control of vi...

Inspired by the human visual system, visual attention (VA) models seem to provide solutions to problems of semantic image understanding by selecting only a small but representative fraction of visual input to process. Having proposed a spatiotemporal VA model for video processing in the past, we propose considerable enhancements in this paper, including the use of steerable filters for 3D orien...

Video surveillance has significant application prospects such as security, law enforcement, and traffic monitoring. Visual traffic surveillance using computer vision techniques can be non-invasive, cost effective, and automated. Detecting and recognizing the objects in a video is an important part of many video surveillance systems which can help in tracking of the detected objects and gatherin...

OBJECTIVE To investigate the reliability of inspection-based classification of sagittal gait patterns in children with bilateral spastic cerebral palsy (CP). METHOD Video clip recordings of gait patterns and sagittal kinematic data obtained by a computerized motion analysis system from 91 patients with bilateral spastic CP were reviewed. The abnormal gait patterns were classified into 4 group...