86 citations · 543 across the 30 of their papers we have counts for
7 papers · 1 filter
Finding Temporally Consistent Occlusion Boundaries in Videos using Geometric Context
S. Hussain Raza, Ahmad Humayun, Matthias Grundmann +2
We present an algorithm for finding temporally consistent occlusion boundaries in videos to support segmentation of dynamic scenes. We learn occlusion boundaries in a pairwise Mark…
Geometric Context from Videos
S. Hussain Raza, Matthias Grundmann, Irfan Essa
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 ca…
Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries
S. Hussain Raza, Omar Javed, Aveek Das +3
We present an algorithm to estimate depth in dynamic video scenes. We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric contex…
Leveraging Context to Support Automated Food Recognition in Restaurants
Vinay Bettadapura, Edison Thomaz, Aman Parnami +2
The pervasiveness of mobile cameras has resulted in a dramatic increase in food photos, which are pictures reflecting what people eat. In this paper, we study how taking pictures o…
Egocentric Field-of-View Localization Using First-Person Point-of-View Devices
Vinay Bettadapura, Irfan Essa, Caroline Pantofaru
We present a technique that uses images, videos and sensor data taken from first-person point-of-view devices to perform egocentric field-of-view (FOV) localization. We define egoc…
Augmenting Bag-of-Words: Data-Driven Discovery of Temporal and Structural Information for Activity Recognition
Vinay Bettadapura, Grant Schindler, Thomaz Plotz +1
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 st…
Predicting Daily Activities From Egocentric Images Using Deep Learning
Daniel Castro, Steven Hickson, Vinay Bettadapura +4
We present a method to analyze images taken from a passive egocentric wearable camera along with the contextual information, such as time and day of week, to learn and predict ever…