Predictive Visual Context in Object Detection View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2003-06-18

AUTHORS

Lucas Paletta

ABSTRACT

This work discriminates external and internal visual context according to a recently determined terminology in computer vision. It is conceptually based on psychological findings in human perception that stress the utility of visual context in object detection processes. The paper outlines a machine vision detection system that analyzes external context and thereby gains prospective information from rapid scene analysis in order to focus attention on promising object locations. A probabilistic framework is defined to predict the occurrence of object detection events in video in order to significantly reduce the computational complexity involved in extensive object search. Internal context is processed using an innovative method to identify the object’s topology from local object features. The rationale behind this methodology is the development of a generic cognitive detection system that aims at more robust, rapid and accurate event detection from streaming video. Performance implications are analyzed with reference to the application of logo detection in sport broadcasts and provide evidence for the crucial improvements achieved from the usage of visual context information. More... »

PAGES

245-258

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/3-540-44958-2_20

DOI

http://dx.doi.org/10.1007/3-540-44958-2_20

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1044645347


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