Discovering object instances from scenes of Daily Living

Hongwen Kang, Martial Hebert, Takeo Kanade

Abstract: We propose an approach to identify and segment objects from scenes that a person (or robot) encounters in Activities of Daily Living (ADL). Images collected in those cluttered scenes contain multiple objects. Each image provides only a partial, possibly very different view of each object. An object instance discovery program must be able to link pieces of visual information from multiple images and extract the consistent patterns.