/People Image Analysis Consortium

People Image Analysis Consortium

The People Image Analysis (PIA) Consortium develops and distributes technologies that process images and videos to detect, track, and understand peoples’ faces, bodies, and activities. The areas of technology that the PIA Consortium focus on include detection and tracking of humans, face recognition, facial expression analysis, gait analysis, and activity recognition. The goal of the Consortium is to develop a comprehensive set of imaging and processing tools, systems, and subsystems that work in the real-world environment.

Please see our official homepage for further information.

Displaying 66 Publications

A cylindrical model-based algorithm recovers the full motion (3D rotations and 3D translations) of...

Many varieties of algorithms for fitting Cootes and Taylor's "Active Appearance Models" are develo...

We are developing the Camera Assisted Meeting Event Observer (CAMEO) - a sensory system designed t...

Our event detection method can detect a wide range of actions in video by correlating spatio-tempo...

This face alignment method detects generic frontal faces with large appearance variations and 2D p...

A 2-D and 3-D model-based tracking method can track a human hand rapidly moving and deformed on co...

A Unifying Framework for Image Alginment

Our multi-people tracking method can automatically initialize and terminate paths of people and fo...

This method can detect cars with occlusions and varying viewpoints from a single still images by u...

A database of 41,368 images of 68 people with Pose, Illumination, and Expression variation.

A face detection system has an accurate detection rate and real time performance by using an ensem...

A novel camera calibration method can increases not only an accuracy of intrinsic camera parameter...

A two-step approach temporally segment facial gestures from video sequences. It can register the r...

cooperative multi-sensor military surveillance system

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