arXiv subjects

Balakrishnan Prabhakaran

Publications and source records attributed to Balakrishnan Prabhakaran.

22 records · Page 2Linked to original sources

arXiv2021

Haptic-enabled Mixed Reality System for Mixed-initiative Remote Robot Control

Robots assist in many areas that are considered unsafe for humans to operate. For instance, in handling pandemic diseases such as the recent Covid-19 outbreak and other outbreaks like Ebola, robots can assist in reaching areas dangerous for humans and do simple tasks such as pick up the correct medicine (among a set of bottles prescribed) and deliver to patients. In such cases, it might not be good to rely on the fully autonomous operation of robots. Since many mobile robots are fully functional with low-level tasks such as grabbing and moving, we consider the mixed-initiative control where the user can guide the robot remotely to finish such tasks. For this mixed-initiative control, the user controlling the robot needs to visualize a 3D scene as seen by the robot and guide it. Mixed reality can virtualize reality and immerse users in the 3D scene that is reconstructed from the real-world environment. This technique provides the user more freedom such as choosing viewpoints at view time. In recent years, benefiting from the high-quality data from Light Detection and Ranging (LIDAR) and RGBD cameras, mixed reality is widely used to build networked platforms to improve the performance of robot teleoperations and robot-human collaboration, and enhanced feedback for mixed-initiative control. In this paper, we proposed a novel haptic-enabled mixed reality system, that provides haptic interfaces to interact with the virtualized environments and give remote guidance for mobile robots towards high-level tasks. The experimental results show the effectiveness and flexibility of the proposed haptic enabled mixed reality system.

cs.RO↗

arXiv2019

Report of 2017 NSF Workshop on Multimedia Challenges, Opportunities and Research Roadmaps

With the transformative technologies and the rapidly changing global R&D landscape, the multimedia and multimodal community is now faced with many new opportunities and uncertainties. With the open source dissemination platform and pervasive computing resources, new research results are being discovered at an unprecedented pace. In addition, the rapid exchange and influence of ideas across traditional discipline boundaries have made the emphasis on multimedia multimodal research even more important than before. To seize these opportunities and respond to the challenges, we have organized a workshop to specifically address and brainstorm the challenges, opportunities, and research roadmaps for MM research. The two-day workshop, held on March 30 and 31, 2017 in Washington DC, was sponsored by the Information and Intelligent Systems Division of the National Science Foundation of the United States. Twenty-three (23) invited participants were asked to review and identify research areas in the MM field that are most important over the next 10-15 year timeframe. Important topics were selected through discussion and consensus, and then discussed in depth in breakout groups. Breakout groups reported initial discussion results to the whole group, who continued with further extensive deliberation. For each identified topic, a summary was produced after the workshop to describe the main findings, including the state of the art, challenges, and research roadmaps planned for the next 5, 10, and 15 years in the identified area.

cs.MM↗

arXiv2016

mPDF: Framework for Watermarking PDF Files using Image Watermarking Algorithms

The advancement in digital technologies have made it possible to produce perfect copies of digital content. In this environment, malicious users reproduce the digital content and share it without compensation to the content owner. Content owners are concerned about the potential loss of revenue and reputation from piracy, especially when the content is available over the Internet. Digital watermarking has emerged as a deterrent measure towards such malicious activities. Several methods have been proposed for copyright protection and fingerprinting of digital images. However, these methods are not applicable to text documents as these documents lack rich texture information which is abundantly available in digital images. In this paper, a framework (mPDF) is proposed which facilitates the usage of digital image watermarking algorithms on text documents. The proposed method divides a text document into texture and non-texture blocks using an energy-based approach. After classification, a watermark is embedded inside the texture blocks in a content adaptive manner. The proposed method is integrated with five known image watermarking methods and its performance is studied in terms of quality and robustness. Experiments are conducted on documents in 11 different languages. Experimental results clearly show that the proposed method facilitates the usage of image watermarking algorithms on text documents and is robust against attacks such as print & scan, print screen, and skew. Also, the proposed method overcomes the drawbacks of existing text watermarking methods such as manual inspection and language dependency.

cs.MM↗

arXiv2016

Region Graph Based Method for Multi-Object Detection and Tracking using Depth Cameras

In this paper, we propose a multi-object detection and tracking method using depth cameras. Depth maps are very noisy and obscure in object detection. We first propose a region-based method to suppress high magnitude noise which cannot be filtered using spatial filters. Second, the proposed method detect Region of Interests by temporal learning which are then tracked using weighted graph-based approach. We demonstrate the performance of the proposed method on standard depth camera datasets with and without object occlusions. Experimental results show that the proposed method is able to suppress high magnitude noise in depth maps and detect/track the objects (with and without occlusion).

cs.CV↗