Detecting Carried Objects in Short Video Sequences

Dima Damen, David Hogg

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

24 Citations (Scopus)


We propose a new method for detecting objects such as bags carried by pedestrians depicted in short video sequences. In common with earlier work [1, 2] on the same problem, the method starts by averaging aligned foreground regions of a walking pedestrian to produce a representation of motion and shape (known as a temporal template) that has some immunity to noise in foreground segmentations and phase of
the walking cycle. Our key novelty is for carried objects to be revealed by comparing the temporal templates against view-specific exemplars generated offline for unencumbered pedestrians. A likelihood map obtained from this match is combined in a Markov random field with a map of prior probabilities for carried objects and a spatial continuity assumption, from which we obtain a segmentation of carried objects using the MAP solution. We have re-implemented the earlier state of the art method [1] and demonstrate a substantial improvement in performance for the new method on the challenging PETS2006 dataset [3]. Although developed for a specific problem, the method could be applied to the detection of irregularities in appearance for other categories of object that
move in a periodic fashion.
Original languageEnglish
Title of host publicationEuropean Conference on Computer Vision (ECCV)
PublisherSpringer Verlag
Number of pages167
ISBN (Print)978-3-540-88689-1
Publication statusPublished - 2008


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