A Multi-view Camera Model for Line-Scan Cameras with Telecentric Lenses

We propose a novel multi-view camera model for line-scan cameras with telecentric lenses. The camera model supports an arbitrary number of cameras and assumes a linear relative motion with constant velocity between the cameras and the object. We distinguish two motion configurations. In the first configuration, all cameras move with independent motion vectors. In the second configuration, the cameras are mounted rigidly with respect to each other and therefore share a common motion vector. The camera model can model arbitrary lens distortions by supporting arbitrary positions of the line sensor with respect to the optical axis. We propose an algorithm to calibrate a multi-view telecentric line-scan camera setup. To facilitate a 3D reconstruction, we prove that an image pair acquired with two telecentric line-scan cameras can always be rectified to the epipolar standard configuration, in contrast to line-scan cameras with entocentric lenses, for which this is possible only under very restricted conditions. The rectification allows an arbitrary stereo algorithm to be used to calculate disparity images. We propose an efficient algorithm to compute 3D coordinates from these disparities. Experiments on real images show the validity of the proposed multi-view telecentric line-scan camera model

A camera model for cameras with hypercentric lenses and some example applications

We propose a camera model for cameras with hypercentric lenses. Because of their geometry, hypercentric lenses allow to image the top and the sides of an object simultaneously. This makes them useful for certain inspections tasks, for which otherwise multiple images would have to be acquired and stitched together. After describing the projection geometry of hypercentric lenses, we derive a camera model for hypercentric lenses that is intuitive for the user. Furthermore, we describe how to determine the parameter values of the model by calibrating the camera with a planar calibration object. We also apply our camera model to two example applications: in the first application, we show how two cameras with hypercentric lenses can be used for dense 3D reconstruction. For an efficient reconstruction, the images are rectified such that corresponding points occur in the same image row. Standard rectification methods would result in perspective distortions in the images that would prevent stereo matching algorithms from robustly establishing correspondences. Therefore, we propose a new rectification method for objects that are approximately cylindrical in shape, which enables a robust and efficient reconstruction. In the second application, we show how to unwrap cylindrical objects to simplify further inspection tasks. For the unwrapping, the pose of the cylinder must be known. We show how to determine the pose of the cylinder based on a single camera image and based on two images of a stereo camera setup

Automist - A Tool for Automated Instruction Set Characterization of Embedded Processors

The steadily increasing performance of mobile devices also implies a rise in power consumption. To counteract this trend it is mandatory to accomplish software power optimizations based on accurate power consumption models characterized for the processor. This paper presents an environment for automated instruction set characterization based on physical power measurements. Based on a detailed instruction set description a testbench generator creates all needed test programs for a complete characterization. Afterwards those programs are executed by the processor and the energy consumption is measured. For an accurate energy measurement a high performance sampling technique has been established, which can be either clock or energy driven

Methodologies for Designing Power-Aware Smart Card Systems

Smart cards are some of the smallest computing platforms in use today. They have limited resources, but a huge number of functional requirements. The requirement for multi-application cards increases the demand for high performance and security even more, whereas the limits given by size and energy consumption remain constant. We describe new methodologies for designing and implementing entire systems with regard to power awareness and required performance. To make use of this power-saving potential, also the higher layers of the system - the operating system layer and the application domain layer - are required to be designed together with the rest of the system. HW/SW co-design methodologies enable the gain of system-level optimization. The first part presents the abstraction of smart cards to optimize system architecture and memory system. Both functional and transactional-level models are presented and discussed. The proposed design flow and preliminary results of the evaluation are depicted. Another central part of this methodology is a cycle-accurate instruction-set simulator for secure software development. The underlaying energy model is designed to decouple instruction and data dependent energy dissipation, which leads to an independent characterization process and allows stepwise model refinement to increase estimation accuracy. The model has been evaluated for a high-performance smart card CPU and an use-case for secure software is given

Compiler-based Software Power Peak Elimination on Smart Card Systems

RF-powered smart cards are widely used in different application areas today. For smart cards not only performance is an important attribute, but also the power consumed by a given application. The power consumed is heavily depending on the software executed on the system. The power profile, especially the power peaks, of an executed application influence the system stability and security. Flattening the power profile can thus increase the stability and security of a system. In this paper we present an optimization system that allows a reduction of power peaks based on a compiler optimization. The optimizations are done on different levels of the compiler. In the backend of the compiler we present new instruction scheduling algorithms. On the intermediate language level we propose the use of iterative compiling for reducing critical peaks

Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints

Biomimetic, dexterous robotic hands have the potential to replicate much of the tasks that a human can do, and to achieve status as a general manipulation platform. Recent advances in reinforcement learning (RL) frameworks have achieved remarkable performance in quadrupedal locomotion and dexterous manipulation tasks. Combined with GPU-based highly parallelized simulations capable of simulating thousands of robots in parallel, RL-based controllers have become more scalable and approachable. However, in order to bring RL-trained policies to the real world, we require training frameworks that output policies that can work with physical actuators and sensors as well as a hardware platform that can be manufactured with accessible materials yet is robust enough to run interactive policies. This work introduces the biomimetic tendon-driven Faive Hand and its system architecture, which uses tendon-driven rolling contact joints to achieve a 3D printable, robust high-DoF hand design. We model each element of the hand and integrate it into a GPU simulation environment to train a policy with RL, and achieve zero-shot transfer of a dexterous in-hand sphere rotation skill to the physical robot hand.Comment: for project website, see https://srl-ethz.github.io/get-ball-rolling/ . for video, see https://youtu.be/YahsMhqNU8o . Submitted to the 2023 IEEE-RAS International Conference on Humanoid Robot

Outcome after resection of Adrenocortical Carcinoma liver metastases: a retrospective study

Background: Metastatic Adrenocortical Carcinoma (ACC) is a rare malignancy with a poor 5-year-survival rate (<15%). A surgical approach is recommended in selected patients if complete resection of distant metastasis can be achieved. To date there are only limited data on the outcome after surgical resection of hepatic metastases of ACC. Methods: A retrospective analysis of the German Adrenocortical Carcinoma Registry was conducted. Patients with liver metastases of ACC but without extrahepatic metastases or incomplete tumour resection were included. Results: Seventy-seven patients fulfilled these criteria. Forty-three patients underwent resection of liver metastases of ACC. Complete tumour resection (R0) could be achieved in 30 (69.8%). Median overall survival after liver resection was 76.1 months in comparison to 10.1 months in the 34 remaining patients with unresected liver metastases (p < 0.001). However, disease free survival after liver resection was only 9.1 months. Neither resection status (R0/R1) nor extent of liver resection were significant predictive factors for overall survival. Patients with a time interval to the first metastasis/recurrence (TTFR) of greater than 12 months or solitary liver metastases showed significantly prolonged survival. Conclusions: Liver resection in the case of ACC liver metastases can achieve long term survival with a median overall survival of more than 5 years, but disease free survival is short despite metastasectomy. Time to recurrence and single versus multiple metastases are predictive factors for the outcome