A Survey on Infrared Imaging with Focus on Human Tracking

1. ECE 671: A Survey on Infrared Imaging with Focus on Human Tracking.  ECE 671 – SPRING 2004 Final Presentation Presented by Nikhil Arun Naik

2. About this Presentation... • Objective of the project. • Achievements of this Semester. • Conclusions. • Future work.

3. Objective of the Project... • Objective of the project as defined at the start of the semester was to conduct A Survey on Infrared Imaging with focus on Human Tracking. • Conduct a survey on Infrared Imaging and present a review on the history of infrared imaging, the techniques involved in infrared imaging and on all the known applications of infrared imaging. • Survey papers and websites specifically on the topic Human Tracking using Infrared Imaging and give a complete review on the techniques and approaches employed in human tracking and on human tracking systems built and used till now by others. • Survey papers and websites on the calibration techniques for thermal cameras and present a brief review on them.

4. Achievements of this Semester... • Infrared Imaging • What is Infrared? Infrared is a band of energy in the 2mm to 100mm wavelength range in the electromagnetic spectrum. • The visible spectrum lies only in the range of wavelengths from 0.4mm to 0.7mm. The band of energy above this in the EM is the IR spectrum and the band of energy below the visible spectrum is the UV spectrum. • Infrared light behaves very much similar to the visible light. It travels at the speed of light (2.988 X 108 m/s) and it to can be reflected, refracted, absorbed and emitted. • An infrared image is a pattern generated proportional to a temperature function corresponding to the area or the object that is being imaged.

5. Achievements of this Semester... • Infrared Imaging • An infrared image is obtained based on the principle that vibration and rotation of atoms and molecules in an object causes the object to give out heat which is captured by an infrared sensor to give us an image. • The Stefan – Boltzmann’s law Infrared Power ~ (T object) 4 • Hence we can infer from that the output power of the object would tend to increase very fast with increase in absolute temperature of the object.

6. Achievements of this Semester... • 3 Major areas of applications of Infrared Imaging. • Monitoring Purposes. • Research and Development. • General Industrial applications.

7. Achievements of this Semester... • General applications of Infrared Imaging • Night vision capabilities to see objects in the absence of light. • Face recognition and Pattern recognition techniques. • In case of fire related disasters used to detect leaks, fire, see through smoke and search for victims. • In naval operations to look for possible oil spillage and threat from enemy vessels in the dark. • Infrared imaging is of greatest use in the maintenance industry where it finds use in predictive maintenance techniques

8. Achievements of this Semester... • Law Enforcement Thermographers Association(LETA) :- Acknowledges 11 applications of Infrared Imaging for Law enforcement purposes. • Hidden Compartments. • Perimeter surveillance. • Marine and ground surveillance. • Structure profiles. • Officer safety. • Distributed surface scenarios. • Environmental. • Flight safety. • Fugitive searches and rescue missions. • Vehicle pursuits.

9. Achievements of this Semester... • Human Tracking. • No one single model can represent all the features we are looking for. • Human tracking has been generally done using visual sensors. But there are many problems associated with this. • The characteristics of a thermal image for humans are uniform for nearly the entire population. • Thermal sensors outperform vision sensors in conditions of poor lighting and visibility.

10. Achievements of this Semester... • Human Tracking. • It is easy to track humans in the dark using infrared imaging since the heat emitted by the humans and the background area will be different and so this difference will show up distinctly. • But the task is not as straight forward because we will have to device an algorithm that takes into account other sources of heat like objects other than human beings. Also the problem of occlusion needs to be taken are of. • Thus the main goal of a human tracking system is to accurately detect and track the presence of human beings in a given field of view in an extremely cost-efficient manner.

11. Achievements of this Semester... • Human Tracking. • The major task involved in human tracking is to firstly detect motion, then confirm that the motion is caused by a human and then to continuously track that persons motion. • Major techniques usually employed are motion detection, background subtraction and template matching. • Human tracking finds major applications in search and surveillance operations.

12. Achievements of this Semester... • Human Tracking using an Infrared sensor array [Feller 2002] • Sensor network consisting of large number of low cost motion sensors and a small number of image sensors for target registration. • Employs the Back Propagation algorithm. • Has a superior range of coverage as compared to a single sensor network.

13. Achievements of this Semester... • Human Tracking using single Infrared sensor [Nakamura 2001] • Here the technique applied is of Background abstraction. • Obtain the foreground image by subtracting background image from the original data and track moving objects. • Discusses the pros and cons of human tracking using normal video against infrared video.

14. Achievements of this Semester... • New Night Visionary Pedestrian Detection and Display Systems[Fang] • Here they have implemented a two-step static pedestrian segmentation algorithm. • In the first step they segment images around hot spots to obtain the humans in the image. This may give some errors from other hot spots in the image like car headlights and lamp posts. • In the second step they try to eliminate these errors using similarity feature comparison by employing a template.

15. Achievements of this Semester... • Pedestrian Detection and Tracking with Night Vision [Xu 2002] • Here they employ a two step approach for detection and tracking. • Detection is achieved using support vector machines which employs size normalized pedestrian candidates. • Tracking is accomplished using Kalman filter prediction method and the process of mean shift tracking.

16. Achievements of this Semester... • Probabilistic template based pedestrian detection in infrared videos[Nanda 2002] • Here infrared video is used to segment the region of interest. A probabilistic template is used for identifying pedestrians. • Raw data (pixel intensities) have been used to segment regions.

17. Achievements of this Semester... • W4: Who? When? Where? What? a real time system for detecting and tracking people[Haritaoglu 1998] • .It uses a combination of shape analysis and tracking to locate people and their body parts like head, hands, feet or torso. • It creates a model of the appearance of people so that tracking can be achieved through interactions like occlusions. • The system is also capable of tracking multiple targets at a time even with occlusion. • The system detects foreground region in each frame by combining background analysis with simple low level processing of the resulting binary image.

18. Achievements of this Semester... [Haritaoglu 1998] Contd/……….

19. Achievements of this Semester... • Automatic target detection and tracking in forward-looking infrared image sequences using morphological connected operators • [Braga-Neto 1999] • They employ morphological connected operators to extract and track targets of use and to eliminate unwanted clutter. • These operators are designed based on the criteria of general size, connectivity and motion using the spatial intra-frame and temporal inter-frame information.

20. Achievements of this Semester... • Tracking human faces in infrared video[Eveland 2001] • Here they firstly model the skin in thermal IR (exposed skin, covered skin and background). • Next human heads are tracked over a period of time by applying segmentation models to a condensation algorithm.

21. Conclusions and Future Work... • The surveys and reviews on general infrared imaging and its applications, on human tracking using infrared imaging and black body calibrators for thermal cameras were completed. • There is a lot of scope for human tracking systems employing infrared imagery since it adds a whole new dimension to the available security systems if they can operate in the dark at night. • All the tasks scheduled for the semester were successfully accomplished. • Future tasks would involve developing our own algorithm and an infrared imagery based human tracking system on the basis of the knowledge gained from this survey. • The algorithm could employ a combination of a human motion detection technique and a tracking method learnt through this survey.

22. End... • Thank You. • Any