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In this paper, we propose an image segmentation-based algorithm to perform upsampling of noisy low-resolution depth maps using information from the high-resolution color image. The depth map is initially upscaled using standard image interpolation technique, and then refined by a process based on the combination of Normalized Cuts segmentation and various smoothness priors in order to obtain a high...
In this paper we propose a novel real time video sailency detection algorithm based on disorder in Motion Field. The proposed algorithm operates on the basic premise that higher disorder pertains to higher information in the scene. Based on the quantified value of the disorder, salient areas in the video frame are demarcated. In order to achieve real time operational capability, the algorithm operates...
A novel algorithm for Virtual View Synthesis based on Non-Local Means Filtering is presented in this paper. Apart from using the video frames from the nearby cameras and the corresponding perpixel depth map, this algorithm also makes use of the previously synthesized frame. Simple and efficient, the algorithm can synthesize video at any given virtual viewpoint at a faster rate. In the process, the...
An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the...
In this work, we evaluate the performance of the popular dense trajectories approach on first-person action recognition datasets. A person moving around with a wearable camera will actively interact with humans and objects and also passively observe others interacting. Hence, in order to represent real-world scenarios, the dataset must contain actions from first-person perspective as well as third-person...
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