Here at the IU Computer Vision Lab, we employ advanced machine learning and statistical techniques to develop systems that extract and harness the growing wealth of information stored in image collections. Some of our applications include discovering informative attributes to differentiate birds, aiding geologists in locating ice layers, estimating human poses, and even studying visual attention in toddlers.

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In both fields, we are intrigued by visual functionalities that give rise to semantically meaningful interpretations of the visual world. We aspire to develop intelligent algorithms that perform important visual perception tasks such as object recognition, scene categorization, integrative scene understanding, human motion recognition, material recognition, etc. Fei-Fei gave a TED talk.

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