Raghavender Sahdev

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Person following behavior is an important task for social robots. To enable robots to follow a person, we have to track the target in real-time without critical failures. There are many situations where the robot will potentially loose tracking in a dynamic environment, e.g., occlusion, illumination, posechanges, etc. Often, people use a complex tracking(More)
In this paper we present a method for robots to do visual place recognition and categorization. The robot learns from experience and then recognizes previously observed places in known environments and categorizes previously unseen places in new environments. This system has been practically tested with a novel dataset developed by us to validate the(More)
In this paper, we introduce a stereo vision based CNN tracker for a person following robot. The tracker is able to track a person in real-time using an online convolutional neural network. Our approach enables the robot to follow a target under challenging situations such as occlusions, appearance changes, pose changes, crouching, illumination changes or(More)
Forced migration is increasingly becoming a global issue of concern. In this paper, we present an effective model of targeted event detection, as an essential step towards the forced migration detection problem. To date, most of the the approaches deal with the event detection in a general setting with the main objective of detecting the presence or onset(More)
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