@conference {12438,
	title = {The evolution of stochastic grammars for representation and recognition of activities in videos},
	booktitle = {2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)},
	year = {2011},
	month = {2011/11/06/13},
	pages = {688 - 688},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The speaker is one of the privileged many to have been taught syntactic pattern recognition methods by the Late Prof. K.S. Fu. In this talk, I will discuss the evolution of stochastic image grammars from the early seventies to now with a focus on image and video understanding applications.},
	keywords = {activity recognition, activity representation, Conferences, Educational institutions, Grammar, Image analysis, image recognition, image representation, image understanding, pattern recognition, stochastic image grammars, syntactic pattern recognition methods, video signal processing, video understanding, Videos},
	isbn = {978-1-4673-0062-9},
	doi = {10.1109/ICCVW.2011.6130309},
	author = {Chellapa, Rama}
}
@conference {12444,
	title = {Face tracking in low resolution videos under illumination variations},
	booktitle = {2011 18th IEEE International Conference on Image Processing (ICIP)},
	year = {2011},
	month = {2011/09/11/14},
	pages = {781 - 784},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In practical face tracking applications, the face region is often small and affected by illumination variations. We address this problem by using a new feature, namely the Gradient-Logarithmic Field (GLF) feature, in the particle filter framework. The GLF feature is robust under illumination variations and the GLF-based tracker does not assume any model for the face being tracked and is effective in low-resolution video. Experimental results show that the proposed GFL-based tracker works well under significant illumination changes and outperforms some of the state-of-the-art algorithms.},
	keywords = {Adaptation models, Computational modeling, Face, face recognition, face tracking, GLF-based tracker, gradient methods, gradient-logarithmic field feature, illumination variations, lighting, low resolution videos, low-resolution, particle filter, particle filter framework, particle filtering (numerical methods), Robustness, tracking, video signal processing, Videos, Visual face tracking},
	isbn = {978-1-4577-1304-0},
	doi = {10.1109/ICIP.2011.6116672},
	author = {Zou, W.W.W. and Chellapa, Rama and Yuen, P.C.}
}
@conference {12609,
	title = {Stabilization and Mosaicing of Airborne Videos},
	booktitle = {Image Processing, 2006 IEEE International Conference on},
	year = {2006},
	month = {2006/10//},
	pages = {345 - 348},
	abstract = {We present an algorithm for stabilizing low-quality and low-resolution video sequences obtained from UAVs and MAVs flying over a predominantly planar terrain. The problem is important for the processing of videos captured from airborne platforms where most of the image region gives little information about the image-motion. The algorithm consists of approximately aligning the images using phase correlation, then refining the transformation parameters using available optical flow measurements and finally performing a minimization of the image difference by carefully selecting the image regions to make the iterations converge. In the second part of the paper, we describe an algorithm for camera ego-motion estimation by incorporating available metadata along with the video sequence. The availability of metadata such as IMU measurements provides a good initial solution for the camera orientation and helps the iterations converge faster by reducing the search space},
	keywords = {airborne, analysis;image, cameras;, convergence;low-resolution, ego-motion, estimation;iterations, flow, measurement;video, mosaicing;camera, MOTION, resolution;image, segmentation;image, sequence;optical, sequences;video, stabilization;image, video, Videos},
	doi = {10.1109/ICIP.2006.313164},
	author = {Ramachandran, M. and Chellapa, Rama}
}
@conference {11908,
	title = {Pedestrian classification from moving platforms using cyclic motion pattern},
	booktitle = {IEEE International Conference on Image Processing, 2005. ICIP 2005},
	volume = {2},
	year = {2005},
	month = {2005/09//},
	pages = {II- 854-7 - II- 854-7},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper describes an efficient pedestrian detection system for videos acquired from moving platforms. Given a detected and tracked object as a sequence of images within a bounding box, we describe the periodic signature of its motion pattern using a twin-pendulum model. Then a principle gait angle is extracted in every frame providing gait phase information. By estimating the periodicity from the phase data using a digital phase locked loop (dPLL), we quantify the cyclic pattern of the object, which helps us to continuously classify it as a pedestrian. Past approaches have used shape detectors applied to a single image or classifiers based on human body pixel oscillations, but ours is the first to integrate a global cyclic motion model and periodicity analysis. Novel contributions of this paper include: i) development of a compact shape representation of cyclic motion as a signature for a pedestrian, ii) estimation of gait period via a feedback loop module, and iii) implementation of a fast online pedestrian classification system which operates on videos acquired from moving platforms.},
	keywords = {compact shape representation, cyclic motion pattern, data mining, Detectors, digital phase locked loop, digital phase locked loops, feedback loop module, gait analysis, gait phase information, human body pixel oscillations, HUMANS, image classification, Image motion analysis, image representation, image sequence, Image sequences, Motion detection, Object detection, pedestrian classification, pedestrian detection system, Phase estimation, Phase locked loops, principle gait angle, SHAPE, tracking, Videos},
	isbn = {0-7803-9134-9},
	doi = {10.1109/ICIP.2005.1530190},
	author = {Yang Ran and Qinfen Zheng and Weiss, I. and Davis, Larry S. and Abd-Almageed, Wael and Liang Zhao}
}
@article {17293,
	title = {Meeting human needs with new digital imaging technologies},
	journal = {IEEE Multimedia},
	volume = {9},
	year = {2002},
	month = {2002/12//Oct},
	pages = {8 - 14},
	abstract = {It{\textquoteright}s a visual world. Images capture many people{\textquoteright}s thrills, emotions, and concerns. Art can shock or inspire, and family photos are some of our greatest treasures. It{\textquoteright}s not surprising that visual information is a vital component of the new computing. Most people depend on visual input to understand the world around them and as a basis for further creative activities. The popularity of visual media such as photos, short videos, and animations attests to their mainstream acceptance. Digital photos and image-laden Web pages have already become major computing applications, but users still want higher-resolution images and faster downloads},
	keywords = {animation, animations, Computer applications, digital images, digital imaging technologies, Helium, History, HUMANS, Image databases, IMAGE PROCESSING, Photography, photos, software libraries, Videos, visual media, Web pages},
	isbn = {1070-986X},
	doi = {10.1109/MMUL.2002.1041942},
	author = {Shneiderman, Ben}
}
