Eye movements were monitored while participants performed a change detection task with images of natural scenes. An initial and a modified scene image were displayed in alternation, separated by a blank interval (flicker paradigm). In the modified image, a single target object was changed either by deleting that object from the scene or by rotating that object 90 degrees in depth. In Experiment...

A Video Watermarking using Scene Change Detection algorithm is proposed that identifies an approach for protection of information of a video based on wavelet transformation. First, the scene change analysis is used to detect the motion part of the color video. Any random image is selected which is used in the embedding process. That image is converted into its binary image. In the next step the...

C a n l ~ n t hnred indexing and r t t r l~va l of video i s hseorning increasingly important Ln many applicatlanr. Identifying scene (hnngrr and special elfecfr in P video I e n e is In essential pre-requisite for automatic indexing. This paper presents 1 res1 time rlgarilhm, which can deled abrupt Irene changer in campressed domain. It il bared on the number of intorpotsfed ma<robiorkr (MBs) ...

Network-based computing is becoming an increasingly important area of research, whereby computational elements within a distributed infrastructure process/enhance the data that traverses through its path. We refer to these computations as online processing and this paper investigates scene change detection in the context of MBonebased proxies in the network. On-line processing varies from tradi...

In this paper we propose a context sensitive technique for unsupervised change detection in multitemporal satellite images of same scene using Pulse coupled neural network. PCNN is a novel artificial neural network which is developed in 1990 and based on visual cortex of cats. The binary images generated by each iteration of the PCNN algorithm create specific signatures of the scene which are c...

This paper proposes a new method that combines the intensity and motion information to detect scene changes such as abrupt scene changes and gradual scene changes. Two major features are chosen as the basic dissimilarity measures, and selfand cross-validation mechanisms are employed via a static scene test. We also develop a novel intensity statistics model for detecting gradual scenechanges.Ex...

Five metrics for scene change detection in video sequences are presented. Metrics previously applied to this problem are surveyed, and are quantitatively compared to the new metrics. Results show that the proposed metrics are superior.

A new technique for scene change detection using neural networks is proposed to operate on compressed video data obtained with only minimal decoding of video. In this paper various types of neural network structures have been trained and tested on different varieties of video clips. The neural networks are shown to be robust for camera activities and object movements. They gave comparatively go...

A scene change detection method is presented in this paper, which analyzes both auditory and visual information sources and accounts for their inter-relations and coincidence to semantically identify video scenes. Audio analysis focuses on the segmentation of the audio source into three types of semantic primitives, i.e. silence, speech and music. Further processing on speech segments aims at l...