Matthai Philipose
- Publications
- Influence
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IEEE International Conference on Robotics and…
We analyze whether radio frequency identification (RFID) technology can be used to improve the localization of mobile robots and persons in their environment. In particular we study the problem of… Continue Reading
Ninth IEEE International Symposium on Wearable…
In this paper we present results related to achieving finegrained activity recognition for context-aware computing applications. We examine the advantages and challenges of reasoning with globally… Continue Reading
We study activity recognition using 104 hours of annotated data collected from a person living in an instrumented home. The home contained over 900 sensor inputs, including wired reed switches,… Continue Reading
IEEE 11th International Conference on Computer…
We propose an approach to activity recognition based on detecting and analyzing the sequence of objects that are being manipulated by the user. In domains such as cooking, where many activities… Continue Reading
We consider applying computer vision to video on cloud-backed mobile devices using Deep Neural Networks (DNNs). The computational demands of DNNs are high enough that, without careful resource… Continue Reading
Abstract We present the design of DyC, a dynamic-compilation system for C based on run-time specialization. Directed by a few declarative user annotations that specify the variables and code on which… Continue Reading
A fundamental difficulty in recognizing human activities is obtaining the labeled data needed to learn models of those activities. Given emerging sensor technology, however, it is possible to view… Continue Reading
Video cameras are pervasively deployed for security and smart city scenarios, with millions of them in large cities worldwide. Achieving the potential of these cameras requires efficiently analyzing… Continue Reading
Large volumes of videos are continuously recorded from cameras deployed for traffic control and surveillance with the goal of answering "after the fact" queries: identify video frames with objects of… Continue Reading
We explore a dense sensing approach that uses RFID sensor network technology to recognize human activities. In our setting, everyday objects are instrumented with UHF RFID tags called WISPs that are… Continue Reading