Olexa Bilaniuk

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This paper presents an embedded implementation of a face detection method based on boosted LBP features for Single Instruction Multiple Data (SIMD) architectures. The implementation exploits parallelism and data reuse in the detection algorithm and is integrated into CogniVue's Gen-1 APEX platform, which uses a SIMD design and is extremely energy efficient.(More)
We consider deep multi-layered generative models such as Boltzmann machines or Hopfield nets in which computation (which implements inference) is both recurrent and stochastic, but where the recurrence is not to model sequential structure, only to perform computation. We find conditions under which a simple feedforward computation is a very good(More)
This work analyzes the problem of homography estimation for robust target matching in the context of real-time mobile vision. We present a device-friendly implementation of the Gaussian Elimination algorithm and show that our optimized approach can significantly improve the homography estimation step in a hypothesize-and-verify scheme. Experiments are(More)
A major drawback of backpropagation through time (BPTT) is the difficulty of learning long-term dependencies, coming from having to propagate credit information backwards through every single step of the forward computation. This makes BPTT both computationally impractical and biologically implausible. For this reason, full backpropagation through time is(More)
The present paper is concerned with the problem of robust pose estimation for planar targets in the context of real-time mobile vision. For robust recognition of targets at very low computational costs, we employ feature-based methods which are based on local binary descriptors allowing fast feature matching at run time. The matching set is then fed to a(More)
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