u niversiteit van a msterdam ias intelligent autonomous systems 1 m. hofmann prof. dr. d. m. gavrila...
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
M. HofmannProf. Dr. D. M. Gavrila
Intelligent Systems LaboratoryInformatics Institute, Faculty of ScienceUniversity of AmsterdamWeb: www.gavrila.net
Looking at People - Detecting People in Images by their Body Parts
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
motion capture foranimation and games
surveillance (i.e. CASSANDRA system,see afternoon presentation)
roboticpets
motion analysis (sports, medical)
pedestrian protection
smart homes, elderly care
Motivation for People Detection
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
Project (Sub)Tasks
Detect people in images by
1. identifying regions of interest (ROIs)
2. detecting individual body parts (faces, head-shoulders, upper bodies, lower bodies)
3. combining results of individual body part-detectors
(This also is possible work-breakdown of 3 person DOAS team)
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
1. Identifying ROIs: Background Modeling
Source: P. Withagen (UvA)
• adjacent frame difference• mean & threshold• mean & covariance
(single Gaussian)• mixture of Gaussians• Kalman filtering
Pixel-based methods
• „Time of Day“: gradual illumination changes• „Waving trees“: background can vacillate • „Shadows“• „Camouflage“• „Initialisation“
Challenges
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
2. Detecting Individual Body Parts
• Use of machine learning techniques
• Viola & Jones approach (ICCV’2003): use Haar wavelet features
with AdaBoost cascade
hypotheses
classifier stag
e 2
classifier stag
e 1
classifier stag
e N
accepted hypotheses(detections)
hypotheseshypotheses
rejected hypotheses
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
3. Combine Results of Individual Part-Detectors
• [Mohan2001, Wu2005]: fixed spatial layout, combination of contribution of individual part-detectors by weighted sum or by additional classifier
• [Mikolajczyk2004, Micilotta2005]: spatial distribution is learnt, estimation of joint probabilities
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
Various
• Intel OpenCV Library, 2007 http://www.intel.com/technology/computing/opencv/index.htm for image filtering, individual body-part detectors, etc.
• LibSVM, a library for Support Vector Machine classification http://www.csie.ntu.edu.tw/~cjlin/libsvm/
• Daimler Image Label Tool, ROC utilities
Dataset
• Training: already pre-trained V&J cascade detectors: OpenCV, UvA any others from the web?
• Test: CASSANDRA dataset (about 5000 images, partially labeled, consider only fully visible people)
System development under MS Visual Studio C++ environment.Use of following libraries / utilities:
Software
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UNIVERSITEITVAN
AMSTERDAM
IASINTELLIGENTAUTONOMOUSSYSTEMS
Bibliography
• [Gavrila1999] D. M. Gavrila. „The Visual Analysis of Human Movement: A Survey“, Computer Vision and Image Understanding, 73(1):82-98, 1999
• [DOAS2007] S. Korzec, H. Visser and M. Goksun. “Detecting Humans by Combining Human Part-detectors in an Urban Setting”. DOAS Final Project 2007.
• [Viola2003] P. Viola, M.J. Jones and D. Snow. „Detecting Pedestrians using Patterns of Motion and Appearance“. Proc. of ICCV, pp.734-741, Nice, France, 2003.
• [Mohan2001] A. Mohan, C. Papageorgiou and T. Poggio „Example-Based Object Detection in Images by Components“, IEEE Transactions on PAMI, 23 (4), pp. 349-361, 2001.
• [Micilotta2005] A.S. Micilotta, E.J. Ong and R. Bowden. “Detection and Tracking of Humans by Probabilistic Body Part Assembly”. BMVC’05.
• [Wu2005a] B. Wu and R. Nevatia. “Detection of Multiple, Partially Occluded Humans in a Single Image by Bayesian Combination of Edgelet Part Detectors”, ICCV’05.
• [Mikolajczyk2004] K. Mikolajczyk, D. Schmid, A. Zisserman, “Human detection based on a probabilistic assembly of robust part detectors”, Proc. ECCV, Prague, Czech Republic, May 11–14, 2004.