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Field robotics 2025年 4卷 99-137页

作者： Ayoub Raji Danilo Caporale Francesco Gatti Andrea Giove Micaela Verucchi Davide Malatesta Nicola Musiu Alessandro Toschi Silviu Roberto Popitanu Fabio Bagni Massimiliano Bosi Alexander Liniger Marko Bertogna Daniele Morra Francesco Amerotti Luca Bartoli Federico Martello Riccardo Porta University of Modena and Reggio Emilia Italy University of Parma Italy Technology Innovation Institute-Autonomous Robotics Research Center UAE HIPERT srl University of Pisa Italy HIPERT srl Computer Vision Lab ETH Zurich Switzerland

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at an unprecedented speed and in a head-to-head scenario, using independently developed software on open-wheel race cars. This paper presents the complete software architecture used by the team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes, and reach speeds above 75m/s (270km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modeling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed second and third, respectively.

关键词： Automobiles Cameras Laser radar Autonomous vehicles Location awareness Safety Planning Vehicle dynamics Testing Sports Motion planning Environmental monitoring

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LiCAR: pseudo-RGB LiDAR image for CAR segmentation

arXiv

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arXiv 2025年

作者： de Loyola Páez-Ubieta, Ignacio Velasco-Sánchez, Edison P. Puente, Santiago T. AUtomatics RObotics and Artificial Vision Lab IUII: University Institute for Computer Research University of Alicante Crta. San Vicente s/n San Vicente del Raspeig AlicanteE-03690 Spain

With the advancement of computing resources, an increasing number of Neural Networks (NNs) are appearing for image detection and segmentation appear. However, these methods usually accept as input a RGB 2D image. On the other side, Light Detection And Ranging (LiDAR) sensors with many layers provide images that are similar to those obtained from a traditional low resolution RGB camera. Following this principle, a new dataset for segmenting cars in pseudo-RGB images has been generated. This dataset combines the information given by the LiDAR sensor into a Spherical Range Image (SRI), concretely the reflectivity, near infrared and signal intensity 2D images. These images are then fed into instance segmentation NNs. These NNs segment the cars that appear in these images, having as result a Bounding Box (BB) and mask precision of 88% and 81.5% respectively with You Only Look Once (YOLO)-v8 large. By using this segmentation NN, some trackers have been applied so as to follow each car segmented instance along a video feed, having great performance in real world experiments. © 2025, CC BY.

关键词： Image segmentation

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OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

OBJECT DETECTION USING HIERARCHICAL GRAPH-BASED SEGMENTATION

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IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Kim, Jungho Choi, Byeongho Kweon, In-So Multimedia IP Research Center KETI Robotics and Computer Vision Lab. KAIST

ISBN: (纸本)9781479903566

Object detection in real images or videos is challenging because the shapes and sizes of objects vary significantly according to their poses, camera viewing direction, and partial occlusion. Previous detection methods employ sliding-window-based schemes that scan windows across an image, requiring many differently shaped windows to capture shape and size variation. In order to solve this problem, we propose an object detection method using hierarchical graph-based segmentation: color-consistent parts are obtained by part-level segmentation and category-consistent regions are found using object-level segmentation. Thus we can avoid scanning a lot of windows across whole images by using part-level segmentation and robustly detect the objects of various shapes and sizes by using object-level segmentation. In addition, we evaluate detection performance using various classifiers with our detection approach.

关键词： Object detection Object classification Graph-based segmentation

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Support Aggregation via Non-linear Diffusion with Disparity-Dependent Support-Weights for Stereo Matching

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9th Asian Conference on computer vision

作者： Yoon, Kuk-Jin Jeong, Yekeun Kweon, In So Computer Vision Lab. Dept. Information and Communications GIST South Korea Robotics and Computer Vision Lab. KAIST South Korea

ISBN: (纸本)9783642123061

In stereo matching, homogeneous areas, depth continuity areas, and occluded areas need more attention. Many methods try to handle pixels in homogeneous areas by propagating supports. As a result, pixels in homogeneous areas get assigned disparities inferred from the disparities of neighboring pixels. However, at the same time, pixels in depth discontinuity areas get supports from different depths and/or from occluded pixels, and resultant disparity maps are easy to be blurred. To resolve this problem, we propose a non-linear diffusion-based support aggregation method. Supports are iteratively aggregated with the support-weights, while adjusting the support-weights according to disparities to prevent incorrect supports from different depths and/or occluded pixels. As a result, the proposed method yields good results not only in homogeneous areas but also in depth discontinuity areas as the iteration goes on without the critical degradation of performance.

关键词： Pixels

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Coping with stress using social robots as emotion-oriented tool: Potential factors discovered from stress game experiment

Coping with stress using social robots as emotion-oriented t...

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5th International Conference on Social robotics, ICSR 2013

作者： Dang, Thi-Hai-Ha Tapus, Adriana Robotics and Computer Vision Lab. ENSTA-Paristech France

ISBN: (纸本)9783319026749

It is known from psychology that humans cope with stress by either changing stress-induced situations (which is called problemoriented coping strategy) or by changing his/her internal perception about the stress-induced situations (which is called emotion-oriented coping strategy). Social robots, as emerging tools that have abilities to socially interact with humans, can be of great use to help people coping with stress. The paper discusses some recent studies about ways of dealing with stress in stressful situations by using social robots. Moreover, we focus on presenting our experimental design and the discovered factors that can allow social robots to assist humans in dealing with stress in an emotion-oriented manner. © Springer International Publishing 2013.

关键词： Machine design

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Physiological signals in driving scenario: How heart rate and skin conductance reveal different aspects of driver's cognitive load

Physiological signals in driving scenario: How heart rate an...

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International Conference on Physiological Computing Systems, PhyCS 2014

作者： Dang, Thi-Hai-Ha Tapus, Adriana Computer Vision and Robotics Lab. ENSTA-Paris Palaiseau France

ISBN: (纸本)9789897580062

Driver's cognitive load has always been associated with the driver's heart rate activity and his/her skin conductance activity. However, what aspects of cognitive load that these signals relate to have never been clearly studied. This paper presents our preliminary results about the relationship between the different physiological signals (heart rate and skin conductance) and the driver's cognitive load. Via one experiment with simulated car driving environment and one experiment in real flying environment, our data suggests that subjects' heart rate relates to the number of events to be processed by the human driver while the skin conductance relates to the novelty of the driving task. Given the small population involved in these experiments, tests on more subjects are planned and reported in the future. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

关键词： Automobile drivers

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Analysis and query of person-vehicle interactions in homography domain

Analysis and query of person-vehicle interactions in homogra...

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4th ACM International Workshop on Video Surveillance and Sensor Networks, VSSN'06, co-located with the 2006 ACM International Multimedia Conference

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego CA United States

ISBN: (纸本)1595934960

This paper presents an efficient and robust paradigm for analysis and query of moving-object interactions in planar homography *** and vehicle activities/interactions are analyzed for situational awareness by using a multi-perspective *** homography constraints are exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatio-temporal relationships between person-and vehicle-tracks are represented by a semantic event grammar. Semantic-level information of the situation is achieved with the anticipation of possible directions of near-future tracks using piecewise velocity history. An efficient query paradigm is proposed by histogram-based approximation of probability density functions of objects and by quad-tree indexing. Experimental data show promising *** framework can be applied to applications for enhanced situational awareness such as disaster prevention,human interactions in structured environments,and crowd movement analysis in wide-view areas. Copyright 2006 ACM.

关键词： Data reduction

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Globally optimal manhattan frame estimation in real-time

Globally optimal manhattan frame estimation in real-time

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2016 IEEE Conference on computer vision and Pattern Recognition, CVPR 2016

作者： Joo, Kyungdon Oh, Tae-Hyun Kim, Junsik Kweon, In So Robotics and Computer Vision Lab. KAIST Korea Republic of

ISBN: (纸本)9781467388511

Given a set of surface normals, we pose a Manhattan Frame (MF) estimation problem as a consensus set maximization that maximizes the number of inliers over the rotation search space. We solve this problem through a branchand-bound framework, which mathematically guarantees a globally optimal solution. However, the computational time of conventional branch-and-bound algorithms are intractable for real-time performance. In this paper, we propose a novel bound computation method within an efficient measurement domain for MF estimation, i.e., the extended Gaussian image (EGI). By relaxing the original problem, we can compute the bounds in real-time, while preserving global optimality. Furthermore, we quantitatively and qualitatively demonstrate the performance of the proposed method for synthetic and real-world data. We also show the versatility of our approach through two applications: extension to multiple MF estimation and video stabilization.

关键词： Problem solving

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A two-stage multi-view analysis framework for human activity and interactions

A two-stage multi-view analysis framework for human activity...

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2007 IEEE Workshop on Motion and Video Computing, WMVC 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527930

This paper presents a new framework for a multi-stage multi-view approach for human interactions and activity analysis. The analysis is performed in a distributed vision system that synergistically integrate track- and body-level representations across multiple cameras. Our system aims at versatile and easily-deployable system that does not require careful camera calibration. Main contributions of the paper are: (1) context-dependent camera handover for occlusion handling, (2) switching the multi-stage analysis between track- and body-level representations, and (3) a hypothesis-verification paradigm for top-down feedback exploiting spatio-temporal constraints inherent in human interaction. Experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions. Current implementation uses two views, but extension to more views is straightforward. © 2007 IEEE.

关键词： Human computer interaction

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Homography-based analysis of people and vehicle activities in crowded scenes

Homography-based analysis of people and vehicle activities i...

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7th IEEE Workshop on Applications of computer vision, WACV 2007

作者： Park, Sangho Trivedi, Mohan M. Computer Vision and Robotics Research Lab. University of California San Diego San Diego CA 92037

ISBN: (纸本)0769527949

This paper presents an new framework for homographybased analysis of pedestrian-vehicle activity in crowded scenes. Planar homography constraint is exploited to extract view-invariant object features including footage area and velocity of objects on the ground plane. Spatiotemporal relationships between people- and vehicle- tracks are represented by a semantic event. Context awareness of the situation is achieved by the estimated density distribution of objects and the anticipation of possible directions of near-future tracks using piecewise velocity history. Singleview and multi-view based homography mapping options are compared. Our framework can be used to enhance situational awareness for disaster prevention, human interactions in structured environments, and crowd movement analysis at wide regions. © 2007 IEEE.

关键词： Feature extraction

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