Key frames play an important role in video annotation. It is one of the widely used methods for video abstraction as this will help us for processing a large set of video data with sufficient content representation in faster way. In this paper a novel approach for key-frame extraction using entropy value is proposed. The proposed approach classifies frames based on entropy values as global feat...

In this work, we present a handheld video browser that utilizes two methods of search; Concept Search and Keyframe Similarity. Concept Search allows a user to define a query using selected visual concepts and presents the user with a cluster of video segments based on extracted image features using OpponentSIFT. Keyframe Similarity has a dependance on the previous search for input criteria, all...

We propose a framework for detecting, tracking and analyzing non-rigid motion based on learned motion patterns. The framework features an appearance based approach to represent the spatial information and Hidden Markov Models (HMM) to encode the temporal dynamics of the time varying visual patterns. The low level spatial feature extraction is fused with the temporal analysis, providing a unifie...

This paper introduces a complete framework for temporal video segmentation. First, a computationally efficient shot extraction method is introduced, which adopts the normalized graph partition approach, enriched with a non-linear, multiresolution filtering of the similarity vectors involved. The shot boundary detection technique proposed yields high precision (90%) and recall (95%) rates, for a...

In this paper, we describe our participation for high-level feature extraction, automatic search and surveillance event detection at TRECVID 2009 evaluation. In high-level feature extraction, we establish a common feature set for all the predefined concepts, including global features and local features extracted from the keyframes. For the concepts related to person activity, space--time intere...

Surveillance cameras are increasingly prevalent in public places, and security services urgently need to monitor violence real time. However, the current violent-behavior-recognition models focus on spatiotemporal feature extraction, which has high hardware resource requirements can be affected by numerous interference factors, such as background information camera movement. Our experiments hav...

In this paper, the authors propose an effective content-based clustering method for keyframes of news video stories using the Near Duplicate Keyframe (NDK) identification concept. Initially, the authors investigate the near-duplicate relationship, as a content-based visual similarity across keyframes, through the Near-Duplicate Keyframe (NDK) identification algorithm presented. The authors assi...

In this work, a real-time image-based camera tracker is designed for live television production studios. The major concern is to decrease camera tracking expenses by an affordable vision-based approach. First, a dense keyframe model of the static studio scene is generated using image-based dense tracking and bundle adjustment. Online camera tracking is then defined as registration problem betwe...

This paper presents an approach on high-level feature detection within video documents, using a Region Thesaurus. A video shot is represented by a single keyframe and MPEG-7 features are extracted locally, from coarse segmented regions. Then a clustering algorithm is applied on those extracted regions and a region thesaurus is constructed to facilitate the description of each keyframe at a high...

In this work, a real-time image-based camera tracking solution is developed for television broadcasting studio environments. An affordable vision-based system is proposed which can compete with expensive matchmoving systems. The system requires merely commodity hardware: a low cost RGB-D sensor and a standard laptop. The main contribution is avoiding time-evolving drift by tracking relative to ...