Max Mintz
University of Pennsylvania
42 Papers
472 Citations
Max Mintz is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Sensor fusion & Minimax. The author has an hindex of 13, co-authored 42 publications.
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Papers
A stereo confidence metric using single view imagery with comparison to five alternative approaches
TL;DR: In this article, the authors explore using stereo performance on two different images from a single view as a confidence measure for a binocular stereo system incorporating that single view, and explore the performance characteristics of each metric under a variety of conditions.
101
Computational methods for task-directed sensor data fusion and sensor planning
Greg Hager,Max Mintz +1 more
TL;DR: A model of task-directed sensing in which sensors are modeled as noise-contaminated, uncertain measurement systems, and sensing tasks are inodeled by a transforma tion describing the type of information required by the task, a utility function describing sensitivity to error, and a cost function describing time or resource constraints on the system is developed.
Cooperative material handling by human and robotic agents: module development and system synthesis
Julie A. Adams,Ruzena Bajcsy,Jana Kosecka,Vijay Kumar,R. Mandelbaum,Max Mintz,Richard P. Paul,C. Wang,Y. Yamamoto,Xiaoping Yun +9 more
- 05 Aug 1995
TL;DR: Presents a collaborative effort to design and implement a cooperative material handling system by a small team of human and robotic agents in an unstructured indoor environment and stresses both paradigms and testbed experimentation.
Robust filtering and prediction for linear systems with uncertain dynamics: A game-theoretic approach
Christopher Martin,Max Mintz +1 more
TL;DR: In this article, the existence and behavior of game-theoretic solutions for robust linear filters and predictors were examined for m th-order time-varying discrete-time systems with uncertain dynamics.
78
Refined methods for creating realistic haptic virtual textures from tool-mediated contact acceleration data
Heather Culbertson,Joseph M. Romano,Pablo Castillo,Max Mintz,Katherine J. Kuchenbecker +4 more
- 04 Mar 2012
TL;DR: The TexturePad system as mentioned in this paper uses a low-order auto-regressive moving-average (ARMA) model for texture modeling and rendering to generate a stable and spectrally accurate vibration waveform in real time.