Joshua Hernandez

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We analyze the observability of 3-D pose from the fusion of visual and inertial sensors. Because the model contains unknown parameters, such as sensor biases, the problem is usually cast as a mixed filtering/identification, with the resulting observability analysis providing necessary conditions for convergence to a unique point estimate. Most models treat(More)
A 32nm SOI critical path monitor (CPM) that can provide timing measurements to a Digital PLL for dynamic frequency adjustments in the 8-core POWER7+™ microprocessor is described. The CPM calibrates to within 2% of cycle time from nominal to turbo voltages. Its voltage sensitivity is 10mV/bit. It tracks processor temperature sensitivity to within 1.5%(More)
We frame the problem of local representation of imaging data as the computation of minimal sufficient statistics that are invariant to nuisance variability induced by viewpoint and illumination. We show that, under very stringent conditions, these are related to “feature descriptors” commonly used in Computer Vision. Such conditions can be(More)
We analyze the observability of motion estimates from the fusion of visual and inertial sensors. Because the model contains unknown parameters, such as sensor biases, the problem is usually cast as a mixed identification/filtering, and the resulting observability analysis provides a necessary condition for any algorithm to converge to a unique point(More)
The design of attitude determination and control of nanosatellites requires innovative solutions that are low-cost, small in size, and minimized power consumption. The University of Manitoba T-Sat1 project has created a simple complement of sensors and actuators that can provide stable determination and orientation. The linear region of photodiode readings(More)
We propose an extension of popular descriptors based on gradient orientation histograms (HOG, computed in a single image) to multiple views. It hinges on interpreting HOG as a conditional density in the space of sampled images, where the effects of nuisance factors such as viewpoint and illumination are marginalized. However, such marginalization is(More)
The paper introduces a notion of the Laplace operator of a polynomial p in noncommutative variables x = (x 1 ,. .. , x g). The Laplacian Lap[p, h] of p is a polynomial in x and in a non-commuting variable h. When all variables commute we have Lap[p, h] = h 2 ∆ x p where ∆ x p is the usual Laplacian. A symmetric polynomial in symmetric variables will be(More)
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