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A wearable 1920×1080 160-degree object viewpoint recognition SoC is realized on a 6.38mm 2 die with 65nm CMOS technology. This system focuses on enhancing the capability for wide viewpoint and long-distance recognition while reducing the computation of feature matching process. The recognition accuracy is improved from 29% to 94% under full HD resolution for a 50m-far traffic light compared with the performance under VGA (640×480). Object viewpoint prediction (OVP) supports 160-degree object viewpoint differences. 85% of power consumption and 75% of memory bandwidth are reduced via proposed visual vocabulary processor (VVP). 52mW power consumption with 25.9GOPS/mm 2 area efficiency is achieved.

Abstract. We consider a problem of identification of point sources in time dependent advection-diffusion systems with a non-linear reaction term. The linear counterpart of the problem in question can be reduced to solving a system of non-linear algebraic equations via the use of adjoint equations. We extend this approach by constructing an algorithm that solves the problem iteratively to account for the non-linearity of the reaction term. We study the question of improving the quality of source identification by adding more measurements adaptively using the solution obtained previously with a smaller number of measurements.

Abstract-This paper presents a robust and reliable other is the characteristic-based method. Image-based methods block-based method for vanishing line and vanishing point depend on the relation between object's position and detection. The proposed method provides assistance in characteristics in an image. For instance, a VP is assumed to locate construction of a depth map, which is a necessity of 3D scenes.in the middle of an image, which is a central point, the closer the Moreover, the method focuses on the fundamental image objects are toward the central point, the smaller the objects are structural element analysis, and divides them into six shown on the image. Hence, collecting information related with successive steps. Furthermore, complicated mathematic objects and the relationship may determine the trend of the calculation and approximation are replaced by six vanishing line toward the vanishing point. Even so, image-based block-based estimation algorithms. Also, the method is a method [3] is not robust enough on finding the vanishing point regular algorithm design which is suitable for VLSI design on because the estimated results still depends on the numbers of future 3D applications.iterative training and adjustment, and acceptable results consume enormous time. Furthermore, erroneous detections may occur with high probability due to vague object relation such as sparse

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