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Security Surveillance
System
Jeanette Miranda
Continuing work by Peter Schiffman and Zac Kelton
May 17, 2013
ENGN256: Computer Vision
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Indoor Security Surveillance
System
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One static webcam
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Background
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Motion detection and location
Pan, tilt, zoom network camera
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Correlation of motion in static webcam feed to motion in ptz feed
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Track most important motion
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Background, Motion detection and
location
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Both largely the same as mid project presentation
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Background
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Ability to capture clean background image for testing
Grayscale background image
Motion detection and location
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Varying number of objects to track dependent on threshold at
pixel level
Absolute difference between current frame and current
background
 Apply threshold
 Morphological operators to clean up mask
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Camera Calibration
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SURF Feature Detector with FLANN (Fast Library for
Approximate Nearest Neighbors) based matcher
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Center of motion for ip camera from center of feature points
that match to within bounding box of motion on static camera
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Experimented with 2D homography – unsuccessful results
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Limit on how far center of motion for ip camera can move per
frame
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For ip camera to move, need to be minimum distance away
from center (prevent shutter)
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Network Camera
From spec sheet available at: http://www.123securityproducts.com/pz8111w.html
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LAN – NETGEAR Fast Ethernet Switch (FS105) between laptop
and network camera
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Web API for pan, tilt, zoom, mjpg video stream, etc
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Screenshots
Static Camera (white rectangle
bounding box of motion)
IP Camera (white circle
center of motion)
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Screenshots
Static Camera (white rectangle
bounding box of motion)
IP Camera (white circle
center of motion)
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Code
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Multithreaded implementation in C++
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Motion detection and background generation can do more
intensive computation, and then skip frames to compensate
Libraries (opensource):
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Opencv: http://code.opencv.org/projects/opencv/wiki
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CVBlob: https://code.google.com/p/cvblob/
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cURLpp: https://code.google.com/p/curlpp/
Available on GitHub (currently only tested on OSx)
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https://github.com/jcmiranda/SurveillanceSystem
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Future Directions
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More robust motion detection for static camera
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More exploration of different approaches to camera
calibration
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Exploiting knowledge of when the camera moves
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3d calibration rig – opencv support for chessboard?
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Fast motion location on ip camera feed without background to
supplement matching?
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Continuity of motion path
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Tuning delays between moves and minimum offset necessary to
cause a move
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