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Oihana Otaegui

on 20 October 2016

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Transcript of 1qwer

No real-time detection is feasible
1000+ cameras in large CCTV systems
1-10 human visualization

Post-investigation is required to determine location, camera and time of interest events (thefts, abandoned luggage, accidents, etc)

E.g. Underground station Atocha (Madrid)
100+ cameras
2-4 days for finding a visual evidence of a complex event might involve police investigation, iterative extraction of videos from recorder, etc.
+105 researchers (+20 PhD)
International Team
Member of:
Private non Profit Applied Research Centre in Visual Computing, Knowledge Engineering and Communications Technologies
From Industrial Needs
To Research Projects
From Research Results
To Industrial Prototypes / Products
R+D in Computer Vision and Knowledge Engineering for Transport sector
Provide advance services and new technology
Improve process effectiveness through intelligent solutions
Clients: private and public sector
Advance Mobility Solutions
BackOffice Security
ITS and Engineering
Non Intrusive Vehicle counting and classifying

Computer Vision based track Auscultation
Easy Configurable
Reat Time Countung, Clasification and Tracking
Railway track defects
Early detection
Avoid accidents
Automatic report generation
Computer Vision based solution
Easily mounted on commercial trains
Track Auscultation
Lane Departure Warning (LDW)
Collision Avoidance System (CAS)
Traffic Sign Detection (TSD)
Pedestrian Detection (PD)
Driver Attention Detection (DAD)
Lane Departure Warning (LDW)
Collision Avoidance System (CAS)
Traffic Sign Detection (TSD)
Pedestrian Detection (PD)
Driver Attention Detection (DAD)
CCTV Event Detection
Complex events: really those of interest (persons fighting, accident, abandoned luggage…)

Humans can do it, but potentially hundred of cameras, thousands of hours of video

Computers can scan all the video archives, but complex events can not be detected with 100% reliability by computer methods
Hybrid Solution
Computer proposes a number of short clips and the human selects
Post-investigation time can be dramatically reduced
The interface can offer numerous options for type of event, filter by date, camera, etc.
Multiple objects
Full-body only
Person detection & tracking
3D face tracking
Facial expressions
3D face model + expression
Haar face detection
Online Appearance Model (OAM)
tracking and fitting
Fit of 3D facial modes
Face detection
Person detection and tracking
Can be used to detect stops, person running…
Up to 4-5 persons
Core2 Quad 2.5 GHz
Detection 70 ms
Tracking 4 ms
Rao-Blackwellized Data Association Particle Filter (RBDAPF)
Template matching learning
Histogram of Oriented Gradients (HOG)
CPU/GPU capabilities
Probabilistic tracking through time
+ learning each object
Combined detector full-body and head/shoulder at each frame
Person detection & tracking
Person detection and tracking
Viulib® Turning vision into reality
Vicomtech-IK4 has combined in Viulib®, a proprietary computer vision technology, consisting of complex algorithms, software and specialized techniques . An solution that collects, processes, and analyzes real-time video images. Viulib® is an advanced software library that
- Simplifies the building of complex artificial vision solutions
- Reduces time in prototyping phases
- Facilitates technology validation
- Optimizes scalable deployments
- Enables transparent licensing schemes
A flexible collaboration framework for your business needs .
Making the transfer of high-tech computer vision to the real world
quick prototyping facilities for mechanical parts
Visual Odometry is a vision based motion estimation algorithm that estimates the ego-motion of a camera through its environment by evaluating the captured images
Driverless Vehicle Sensoring
Visual Sensors: Odometry, SLAM
SLAM is a technique used by robots and autonomous vehicles to build up a map within an unknown environment , or to update a map within a known environment , while at the same time keeping track of their current location.
Low Cost Real Time Motion Sensor
Visual EgoMotion
2-cameras - stereo vision
EgoMotion estimation and Scena Map building
Full transcript