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Boekema, H.J. (author), Martens, Bruno K.W. (author), Kooij, J.F.P. (author), Gavrila, D. (author)This letter presents View-of-Delft Prediction, a new dataset for trajectory prediction, to address the lack of on-board trajectory datasets in urban mixed-traffic environments. View-of-Delft Prediction builds on the recently released urban View-of-Delft (VoD) dataset to make it suitable for trajectory prediction. Unique features of this...journal article 2024
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de Groot, O.M. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso-Mora, J. (author)Navigating mobile robots through environments shared with humans is challenging. From the perspective of the robot, humans are dynamic obstacles that must be avoided. These obstacles make the collision-free space nonconvex, which leads to two distinct passing behaviors per obstacle (passing left or right). For local planners, such as receding...conference paper 2023
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Roth, M. (author), Gavrila, D. (author)We present intrApose, a novel method for continuous 6 DOF head pose estimation from a single camera image without prior detection or landmark localization. We argue that using camera intrinsics alongside the intensity information is essential for accurate pose estimation. The proposed head pose estimation framework is crop-aware and scale...journal article 2023
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Palffy, A. (author), Kooij, J.F.P. (author), Gavrila, D. (author)Early and accurate detection of crossing pedestrians is crucial in automated driving in order to perform timely emergency manoeuvres. However, this is a difficult task in urban scenarios where pedestrians are often occluded (not visible) behind objects, e.g., other parked vehicles. We propose an occlusion aware fusion of stereo camera and...journal article 2023
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Ding, Fangqiang (author), Palffy, A. (author), Gavrila, D. (author), Lu, Chris Xiaoxuan (author)This work proposes a novel approach to 4D radar-based scene flow estimation via cross-modal learning. Our approach is motivated by the co-located sensing redundancy in modern autonomous vehicles. Such redundancy implicitly provides various forms of supervision cues to the radar scene flow estimation. Specifically, we introduce a multi-task model...conference paper 2023
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Rist, C.B. (author), Emmerichs, David (author), Enzweiler, Markus (author), Gavrila, D. (author)Semantic scene completion is the task of jointly estimating 3D geometry and semantics of objects and surfaces within a given extent. This is a particularly challenging task on real-world data that is sparse and occluded. We propose a scene segmentation network based on local Deep Implicit Functions as a novel learning-based method for scene...journal article 2022
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Roth, M. (author), Stapel, J.C.J. (author), Happee, R. (author), Gavrila, D. (author)We present a novel method for vehicle-pedestrian path prediction that takes into account the awareness of the driver and the pedestrian towards each other. The method jointly models the paths of vehicle and pedestrian within a single Dynamic Bayesian Network (DBN). In this DBN, sub-graphs model the environment and entity-specific context cues...journal article 2022
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Palffy, A. (author), Pool, E.A.I. (author), Baratam, Srimannarayana (author), Kooij, J.F.P. (author), Gavrila, D. (author)Next-generation automotive radars provide elevation data in addition to range-, azimuth- and Doppler velocity. In this experimental study, we apply a state-of-the-art object detector (PointPillars), previously used for LiDAR 3D data, to such 3+1D radar data (where 1D refers to Doppler). In ablation studies, we first explore the benefits of...journal article 2022
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Hehn, T.M. (author), Kooij, J.F.P. (author), Gavrila, D. (author)State-of-the-art stixel methods fuse dense stereo disparity and semantic class information, e.g. from a Convolutional Neural Network (CNN), into a compact representation of driveable space, obstacles and background. However, they do not explicitly differentiate instances within the same semantic class. We investigate several ways to augment...journal article 2022
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Muench, C. (author), Bijelic, Mario (author), Gavrila, D. (author)We show how to design a motion prediction algorithm that works with 3D object detections and map locations. In particular, we obtain object id’s – even though the training data does not contain any object id’s – across multiple time-steps into the future by propagating a Gaussian Mixture of likely object (e.g., vehicle) locations through time.We...conference paper 2022
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Onkhar, V. (author), Bazilinskyy, P. (author), Stapel, J.C.J. (author), Dodou, D. (author), Gavrila, D. (author), de Winter, J.C.F. (author)Non-verbal communication, such as eye contact between drivers and pedestrians, has been regarded as one way to reduce accident risk. So far, studies have assumed rather than objectively measured the occurrence of eye contact. We address this research gap by developing an eye contact detection method and testing it in an indoor experiment with...journal article 2021
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de Groot, O.M. (author), Ferreira de Brito, B.F. (author), Ferranti, L. (author), Gavrila, D. (author), Alonso-Mora, J. (author)We present an optimization-based method to plan the motion of an autonomous robot under the uncertainties associated with dynamic obstacles, such as humans. Our method bounds the marginal risk of collisions at each point in time by incorporating chance constraints into the planning problem. This problem is not suitable for online optimization...journal article 2021
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Muench, C. (author), Oliehoek, F.A. (author), Gavrila, D. (author)Modeling possible future outcomes of robot-human interactions is of importance in the intelligent vehicle and mobile robotics domains. Knowing the reward function that explains the observed behavior of a human agent is advantageous for modeling the behavior with Markov Decision Processes (MDPs). However, learning the rewards that determine...journal article 2021
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Pool, E.A.I. (author), Kooij, J.F.P. (author), Gavrila, D. (author)This paper compares two models for context-based path prediction of objects with switching dynamics: a Dynamic Bayesian Network (DBN) and a Recurrent Neural Network (RNN). These models are instances of two larger model categories, distinguished by whether expert knowledge is explicitly crafted into the state representation (and thus is...journal article 2021
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Domhof, J.F.M. (author), Kooij, J.F.P. (author), Gavrila, D. (author)We address joint extrinsic calibration of lidar, camera and radar sensors. To simplify calibration, we propose a single calibration target design for all three modalities, and implement our approach in an open-source tool with bindings to Robot Operating System (ROS). Our tool features three optimization configurations, namely using error...journal article 2021
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Palffy, A. (author), Dong, Jiaao (author), Kooij, J.F.P. (author), Gavrila, D. (author)This letter presents a novel radar based, single-frame, multi-class detection method for moving road users ( pedestrian, cyclist, car ), which utilizes low-level radar cube data. The method provides class information both on the radar target- and object-level. Radar targets are classified individually after extending the target features with a...journal article 2020
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Rudenko, Andrey (author), Palmieri, Luigi (author), Herman, Michael (author), Kitani, Kris M. (author), Gavrila, D. (author), Arras, Kai O. (author)With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service...review 2020
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Kooij, J.F.P. (author), Flohr, F.B. (author), Pool, E.A.I. (author), Gavrila, D. (author)Anticipating future situations from streaming sensor data is a key perception challenge for mobile robotics and automated vehicles. We address the problem of predicting the path of objects with multiple dynamic modes. The dynamics of such targets can be described by a Switching Linear Dynamical System (SLDS). However, predictions from this...journal article 2019
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Krebs, S.A. (author), Braun, M. (author), Gavrila, D. (author)This paper presents an approach to generate dense person 3D trajectories from sparse image annotations on-board a moving platform. Our approach leverages the additional information that is typically available in an intelligent vehicle setting, such as LiDAR sensor measurements (to obtain 3D positions from detected 2D image bounding boxes) and...conference paper 2019
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Muench, C. (author), Gavrila, D. (author)We propose a novel algorithm that predicts the interaction of pedestrians with cars within a Markov Decision Process framework. It leverages the fact that Q-functions may be composed in the maximum-entropy framework, thus the solutions of two sub-tasks may be combined to approximate the full interaction problem. Sub-task one is the interaction...conference paper 2019
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