Abstract We present an efficient and scalable algorithm for seg- menting 3D RGBD point clouds by combining depth, color, and temporal information using a multistage, hierarchical graph-based approach. Our algorithm processes a moving window over several point clouds to group similar regions over a graph, resulting in an initial over-segmentation. These regions are then merged […]
Abstract We present a novel algorithm for estimating the broad 3D geometric structure of outdoor video scenes. Leveraging spatio-temporal video segmentation, we decompose a dynamic scene captured by a video into geometric classes, based on predictions made by region-classifiers that are trained on appearance and motion features. By examining the homogeneity of the prediction, we […]
Abstract We introduce a new problem domain for activity recognition: the analysis of children’s social and communicative behaviors based on video and audio data. We specifically target interactions between children aged 1-2 years and an adult. Such interactions arise naturally in the diagnosis and treatment of developmental disorders such as autism. We introduce a new […]
Abstract We present data-driven techniques to augment Bag of Words (BoW) models, which allow for more robust modeling and recognition of complex long-term activities, especially when the structure and topology of the activities are not known a priori. Our approach specifically addresses the limitations of standard BoW approaches, which fail to represent the underlying temporal […]
At IEEE CVPR 2012 is in Providence RI, from Jun 16 – 21, 2012. Busy week ahead meeting good friends and colleagues. Here are some highlights of what my group is involved with. Paper in Main Conference K. Kim, D. Lee, and I. Essa (2012), “Detecting Regions of Interest in Dynamic Scenes with Camera Motions,” in […]
Detecting Regions of Interest in Dynamic Scenes with Camera Motions Abstract We present a method to detect the regions of interests in moving camera views of dynamic scenes with multiple mov- ing objects. We start by extracting a global motion tendency that reflects the scene context by tracking movements of objects in the scene. We […]
via Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths – Google Research Blog. Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths Posted by Matthias Grundmann, Vivek Kwatra, and Irfan Essa, Earlier this year, we announced the launch of new features on the YouTube Video Editor, including stabilization for shaky videos, with the ability to preview them in […]
Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths Grundmann, Kwatra, and Essa (2011), “Auto-Directed Video Stabilization with Robust L1 Optimal Camera Paths,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011. [PDF] [WEBSITE][VIDEO] [DEMO][Google Research Blog] [BIBTEX] @inproceedings{2011-Grundmann-AVSWROCP, Author = {M. Grundmann and V. Kwatra and I. Essa}, Booktitle = {Proceedings of IEEE Conference […]
Kihwan Kim, Matthias Grundmann, Ariel Shamir, Iain Matthews, Jessica Hodgins, Irfan Essa (2010) “Motion Field to Predict Play Evolution in Dynamic Sport Scenes” in Proceedings of IEEE Computer Vision and Pattern Recognition Conference (CVPR), San Francisco, CA, USA, June 2010 [PDF][Website][DOI][Video (Youtube)]. Abstract Videos of multi-player team sports provide a challenging domain for dynamic scene analysis. Player actions […]
Discontinuous Seam-Carving for Video Retargeting Matthias Grundmann, Vivek Kwatra, Mei Han, Irfan Essa (2010) “Discontinuous Seam-Carving for Video Retargeting” in Proceedings of IEEE Computer Vision and Pattern Recognition Conference (CVPR), San Francisco, CA, USA, June 2010 [PDF][Website][DOI][Video (Youtube)]. Abstract We introduce a new algorithm for video retargeting that uses discontinuous seam-carving in both space and time for resizing […]