Main Objective

The objective of MODEST is to define and develop a framework for analysing video sequences in order to extract high-level semantic scene interpretation. This will be based on the segmentation, tracking and indexing of moving objects in video scenes and the index interpretation by the use of Intelligent Physical Agents (IPA). The work will be undertaken within the context of the MPEG-4, MPEG-7 and FIPA standards. The results will be demonstrated by means of a video surveillance application.

Technical Approach

Cameras capture raw image sequences. A first step extracts objects from these sequences. A second step uses indexing to extract features from the objects. Finally, content analysis, interpretation and decisions are performed by the camera assistants, standing alone or working together with the application assistant.
The results of the first steps can help to encode the sequences in MPEG-4 format and send them to the user for verification purposes.
To take decisions from video scenes, MODEST uses the following hierarchical approach:
1. Object extraction
a. Physical objects extraction (and transmission) - link with MPEG-4
b. Decomposition of images into regions (low-level segmentation, tracking and layering) - link with COST 211quat
c. High-level grouping of regions into objects with the help of external knowledge
2. Content extraction - link with MPEG-7
a. Automatic extraction of primitive features
b. Semantic features inferred (e.g. through fuzzy reasoning)
3. Content analysis, interpretation and decisions - link with FIPA
a. Reasoning at the camera level, basic scene interpretation
b. Reasoning at the application level: decision, activation of alarms and user interface

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