Authors:
Alessandro Bruno
;
Luca Greco
and
Marco La Cascia
Affiliation:
Università degli studi di Palermo, Italy
Keyword(s):
Object Modeling, Video Query, Object Recognition.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Data Engineering
;
Image and Video Analysis
;
Information Retrieval
;
Object Recognition
;
Ontologies and the Semantic Web
;
Pattern Recognition
;
Software Engineering
;
Video Analysis
Abstract:
In this paper we present a novel technique for object modeling and object recognition in video. Given a set
of videos containing 360 degrees views of objects we compute a model for each object, then we analyze
short videos to determine if the object depicted in the video is one of the modeled objects. The object model
is built from a video spanning a 360 degree view of the object taken against a uniform background. In order
to create the object model, the proposed techniques selects a few representative frames from each video and
local features of such frames. The object recognition is performed selecting a few frames from the query
video, extracting local features from each frame and looking for matches in all the representative frames
constituting the models of all the objects. If the number of matches exceed a fixed threshold the
corresponding object is considered the recognized objects .To evaluate our approach we acquired a dataset
of 25 videos representing 25 different objects
and used these videos to build the objects model. Then we
took 25 test videos containing only one of the known objects and 5 videos containing only unknown objects.
Experiments showed that, despite a significant compression in the model, recognition results are
satisfactory.
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