We define a Spine as a branching axial structure representing the shape and topology of a 3D objects limbs, and capturing the limbs correspondence and motion over time. … In general, our approach combines the objectives of generalized cylinders, 3D scanning, and markerless motion capture to generate baseline models from real puppets, animals, and human subjects.
Vivek Kwatra, Arno Schödl, Irfan Essa, Greg Turk, Aaron Bobick (2003), “Graphcut textures: image and video synthesis using graph cuts” In ACM Transactions on Graphics (TOG), Volume 22 , Issue 3, Proceedings of ACM SIGGRAPH 2003, Pages: 277 – 286, July 2003, ISSN:0730-0301. (DOI|Paper| SIGGRAPH Video (160 MB, 50 MB) | Video Results 87 MB […]
Haro, A. Essa, I. (2002), “Learning video processing by example” In Proceedings of 16th International Conference on Pattern Recognition, 2002, 11-15 Aug. 2002 Volume: 1, page(s): 487 – 491 vol.1, Number of Pages: 4 vol.(xxix 834 xxxv 1116 xxxiii 1068 xxv 418), ISSN: 1051-4651, ISBN: 0-7695-1695-X, [Digital Object Identifier: 10.1109/ICPR.2002.1044771][IEEEXplore#] Abstract We present an algorithm […]
Citation [bibtex key= 2002-Schodl-CAVS] Abstract We introduce a new optimization algorithm for video sprites to animate realistic-looking characters. Video sprites are animations created by rearranging recorded video frames of a moving object. Our new technique to find good frame arrangements is based on repeated partial replacements of the sequence. It allows the user to specify […]
Talk: Invited Speaker at CMU's Robotics Institute (2002): "Temporal Reasoning from Video to Temporal Synthesis of Video"
Irfan Essa, “Temporal Reasoning from Video to Temporal Synthesis of Video” CMU’s Robotics Institute: Seminar, February 15, 2002 Temporal Reasoning from Video to Temporal Synthesis of Video Abstract In this talk, I will present some ongoing work on extracting spatio-temporal cues from video for both synthesis of novel video sequences, and recognition of complex activities. […]
Depth Layers from Occlusions [bibtex file=IrfanEssaWS.bib key=2001-Schodl-DLFO] Abstract We present a method to extract relative depth information from an uncalibrated monocular video sequence. Our method detects occlusions caused by an object moving in a static scene to infer relative depth relationships between scene parts. Our approach does not rely on any strong assumptions about the […]
Citation [bibtex key= 2001-Brostow-IMBSMA] Additional Info Gabriel J. Brostow and Irfan Essa (2001) “Image-based motion blur for stop motion animation” In Proceedings of the 28th annual conference on Computer graphics and interactive techniques (ACM SIGGRPH) Pages: 561 – 566 August 2001, ISBN:1-58113-374-X ACM New York, NY, USA (DOI|PDF|Video|Project Site) Abstract Stop motion animation is a […]
Paper [bibtex file=IrfanEssaWS.bib key=2000-Schodl-VT] Abstract This paper introduces a new type of medium, called a video texture, which has qualities somewhere between those of a photograph and a video. A video texture provides a continuous infinitely varying stream of images. While the individual frames of a video texture may be repeated from time to time, […]
Motion Based Decompositing Video [bibtex file=IrfanEssaWS.bib key=1999-Brostow-MBDV] Abstract We present a method to decompose video sequences into layers that represent the relative depths of complex scenes. Our method combines spatial information with temporal occlusions to determine relative depths of these layers. Spatial information is obtained through edge detection and a customized contour completion algorithm. Activity […]