Objective & Scope:

The objective of this workshop is to highlight cutting edge advances and state-of-the-art work being made in the exponentially growing field of PBVS (previously OTCBVS) along its three main axes: Algorithms, Sensors Processing, and Applications. This field involves deep theoretical research in sub-areas of image processing, machine vision, pattern recognition, machine learning, robotics, and augmented reality within and beyond the visible spectrum. It also presents a suitable framework for building solid advanced vision based systems.

The computer vision community has typically focused mostly on the development of vision algorithms for object detection, tracking, and classification associated with visible range sensors in day and office-like environments. In the last decade, infrared (IR), thermal and other non-visible imaging sensors were used only in special areas like medicine and military. That lower interest level in infrared imagery was due in part to the high cost of non-visible range sensors, low resolutions, poor image quality, lack of widely available data sets, and lack of consideration of the potential advantages of the non-visible part of the spectrum. These historical objections are becoming less relevant as IR imaging technology is advancing rapidly and the sensor cost is dropping dramatically. Image sensing devices with high dynamic range and high IR sensitivity have started to appear in a growing number of applications ranging from military and automotive domains to home and office security. In addition, mobile hyperspectral and mm-wave sensors are also coming into existence.

In order to develop robust and accurate vision-based systems that operate in and beyond the visible spectrum, not only existing methods and algorithms originally developed for the visible range should be improved and adapted, but also entirely new algorithms that consider the potential advantages of non-visible ranges are certainly required. The fusion of visible and non-visible ranges, like radar and IR images, or thermal and visible spectrum images, is another dimension to explore for higher performance of vision-based systems. The non-visible light is widely employed in night vision-based systems, and many detection and recognition systems available today in the market arerelying on physiological phenomena produced by IR and thermal wavelengths. Using artificially controlled lights is a practical solution to eliminate challenging ambient light effects.

This series of OTCBVS/PBVS workshop creates connections between different communities in the machine vision world ranging from public research institutes to private, military, and federal laboratories. It brings together academic pioneers, industrial and military researchers and engineers in the field of computer vision, image analysis, pattern recognition, machine learning, signal processing, sensors, and human-computer interaction.

Topics of Interest:

• Theory and Algorithms
      Target/object classification
      Target/object tracking
      Target/object recognition
      Feature extraction and matching
      Automatic object detection
      Face recognition in IR & thermal images
      SAR image processing
      Depth data processing
• Sensors and Sensor Technology
      Smart systems/sensors
      Combining visible & non-visible signals
      Enhanced detection/tracking/recognition performance using fusion
      Vision augmentation enabling system concepts and components
• Applications
      Medical applications
      Automotive applications
      Military applications
      Avionics systems with augmented vision
      Assisted perception for robotics
      Wide area surveillance and geolocalization

Important Dates :

• Paper Submission: March 29, 2013 (extended)
• Author Notification: April 18, 2013
• Camera Ready Submission: May 1, 2013
• PBVS Workshop: June 24, 2013

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