Continuous global time series of vegetation indices, which are available since early 1980s, are of great value to detect changes in vegetation status at large spatial scales. Most change detection methods, however, assume a fixed change trajectory – defined by the start and end of the time series – and a linear or monotonic trend. Here, we apply a change detection method which detects abrupt ch...

We present in this paper a camera-based system for detecting drowning incidents in a swimming pool at the earliest possible stage. The system consists of two main parts: a vision component which can reliably detect and track swimmers in spite of large scene variations of monitored pool areas, and an event-inference module which parses observation sequences of swimmer features for possible drown...

Analysis of the multi–spectral remotely sensed images of the areas destructed by an earthquake is proved to be a helpful tool for construction assessments. In this paper, we propose a new fast and reliable fuzzy change detection method for multi–spectral images. The proposed fuzzy change detection method is mathematically and experimentally investigated and shown to be efficient and effective.

We explored whether individual features and bindings between those features in VSTM tasks are completely lost from trial to trial or whether residual memory traces for these features and bindings are retained in long-term memory. Memory for arrays of coloured shapes was assessed using change detection or cued recall. Across trials, either the same colour-shape (integrated object) combinations w...

In this paper we perform event analysis on a challenging surveillance dataset without any artificial events. We analyze low-level and high-level features such as motion vectors, change detection and pedestrian detections for recognition of events. We performed detection of three events namely person runs, elevator no entry and opposing flow. The event detection is performed on 60 hours of TRECV...

Perception does not happen instantaneously. Instead, perceptual information is accumulated gradually (i.e., a rise in the perceptual response) to achieve accurate identification despite perceptual noise. This temporal integration of information predicts that previous presentations may become erroneously blended with subsequent presentations. An optimal decision process can reduce this source co...

The widespread use of digital multimedia in applications such as security, surveillance and the semantic web, has made the automated characterization of human activity necessary. In this work, a method for the characterization of multiple human activities based on statistical processing of the video data is presented. First the active pixels of the video are detected, resulting in a binary mask...

We present a systematic approach for the design of change detection and model validation algorithms for dynamical systems. We show bow to associate to any identification algorithm a change detection and a model validation procedure, which are optimal in some asymptotic sense. The foundations of our method go back to the asymptotic local approach in statistics, and our method generalizes this ap...

Analysis of land cover change is one of the major challenges in the remote sensing and GIS domain, especially when multi-temporal or multi-sensor analyses are conducted. One of the reasons is that errors and inaccuracies from multiple datasets (for instance caused by sensor bias or spatial misregistration) accumulate and can lead to a high amount of erroneous change. A promising approach to cou...

A system separating objects moving within a slow changing background is presented. The originality of the approach resides in two related components. First, the change detection robust to camera noise which does not require any sophisticated parametric tuning as it is based on a probabilistic method. Second, the change is detected between a video frame representing a scene at a given time, and ...