CMU | Component Analysis Laboratory

Current projects

	Unification of Component Analysis This project aims to find the fundamental set of equations that unifies all component analysis methods.

	Feature selection Feature selection in component analysis.

	Image alignment Image alignment with parameterized appearance models.

	Low dimensional embeddings Finding low dimensional embeddings of signals for optimal modeling, classification and clustering.

	Learning Optimal Representations Learning optimal representations for classification, image alignment, visualization and clustering.

	Multimodal Diaries Summarization of daily activity from multimodal data (audio, video, body sensors and computer monitoring)

	Facial Feature Detection Detecting facial features in images.

	Facial Expression Analysis Automatic facial expression encoding, extraction and recognition, and expression intensity estimation for diverse applications: teleconferencing, human-computer interaction/interface.

	Temporal Alignment of Human Behavior Temporal alignment of two or more subjects recorded from heterogeneous sensors is a challenging problem. This project develops statistical techniques for spatio-temporal alignment of multidimensional time series.

	Temporal Segmentation of Human Behavior Temporal Segmentation of Human Motion Temporal Segmentation of Facial Behavior

	Face Recognition Recognizing people from images and video.

Past projects

	Camera Assisted Meeting Event Observer We are developing the Camera Assisted Meeting Event Observer (CAMEO) - a sensory system designed to provide an electronic agent with physical awareness of the real world.

	Machine learning approaches to invert the Radiative Transfer Equation Supervised learning approaches to invert the non-linear Radiative Transfer Equation in remote sensing problems.

	Bird Classification Segmentation and classification of birds from images.

	Indoor People Localization Tracking multiple people in indoor environments with the connectivity of Bluetooth devices.