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Author Phillips, P. Jonathon ♦ Sarkar, Sudeep ♦ Robledo, Isidro ♦ Grother, Patrick ♦ Bowyer, Kevin
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Source Code ♦ Increas-ing Difficulty ♦ Challenge Problem ♦ Important Dimension ♦ Video Sequence ♦ Affect Perfor-mance ♦ Data Set ♦ Unix Script ♦ Baseline Algorithm ♦ Humanid Challenge Problem ♦ Probe Video Sequence ♦ Large Set ♦ Baseline Result ♦ Standard Dataset ♦ Human Id Using Gait Analysis ♦ Surface Type ♦ Computer Vision ♦ Research Community ♦ Baseline Al-gorithm ♦ Basic Result
Description Identification of people from gait captured on video has become a challenge problem in computer vision. However, there is not a baseline algorithm or standard dataset for measuring, or determining what factors affect performance. In fact, the conditions under which the problem is “solv-able ” are not understood or characterized. This paper de-scribes a large set of video sequences (about 300 GB of data related to 452 sequences from 74 subjects) acquired to investigate important dimensions of this problem, such as variations due to viewpoint, footwear, and walking sur-face. We introduce the HumanID challenge problem. The challenge problem contains a set of experiments of increas-ing difficulty, a baseline algorithm, and its performance on the challenge problem. Our results suggest that differences in footwear or walking surface type between the gallery and probe video sequence are factors that affect perfor-mance. The data set, the source code for the baseline al-gorithm, and UNIX scripts to reproduce the basic results reported here are available to the research community at
International Conference on Automatic Face and Gesture Recognition
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2002-01-01