Gaurav Srivastava

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—We propose a human activity classification algorithm that has a distributed and lightweight implementation appropriate for wireless camera networks. With input from multiple cameras, our algorithm achieves invariance to the orientation of the actor and to the camera viewpoint. We conceptually describe how the algorithm can be implemented on a distributed(More)
We propose a novel evidence accumulation framework that accurately estimates the positions of humans in a 3D environment. The framework consists of a network of distributed agents having different functionalities. The modular structure of the network allows scalability to large surveillance areas and robust operation. The framework does not assume reliable(More)
We address the problem of predicting category labels for unlabeled videos in a large video dataset by using a ground-truth set of objectively labeled videos that we have created. Large video databases like YouTube require that a user uploading a new video assign to it a category label from a prescribed set of labels. Such category labeling is likely to be(More)
V isual search over large image repositories in real time is one of the key challenges for applications such as mobile visual query-by-capture, augmented reality, and biometrics-based identification. Figure 1 illustrates examples of this new wave of applications enabled by large visual search capabilities. In these applications , search accuracy and(More)
The tumor suppressor gene, Von Hippel-Lindau (VHL), is frequently mutated in the most common form of kidney cancer, clear cell renal cell carcinoma (CCRCC). In hypoxic conditions, or when there is a VHL mutation, the hypoxia inducible factors, HIF1α and HIF2α, are stabilized and transcribe a panel of genes associated with cancer such as vascular endothelial(More)
Thoracoscopic splanchnicectomy has been used for the management of upper abdominal pain syndromes as an alternative to celiac plexus block for conditions such as chronic pancreatitis or supramesocolic malignant neoplasms, including unresectable pancreatic cancer. This procedure is similar to the percutaneous block with a higher degree of precision and(More)
This paper presents Locality-constrained Low Rank Coding (LLRC) as a novel approach for image classification. The widely used Sparse representation based algorithms reconstruct a test sample using a sparse linear combination of training samples. But they do not consider the underlying structure of the data in the feature space. On the other hand, Low Rank(More)
Modeling data as being sampled from a union of independent or disjoint sub-spaces has been widely applied to a number of real world applications. Recently, high dimensional data has come into focus because of advancements in computational power and storage capacity. However, a number of algorithms that assume the aforementioned data model have high time(More)