Peyman Moghadam

Line-based extrinsic calibration of range and image sensors

Creating rich representations of environments requires integration of multiple sensing modalities with complementary characteristics such as range and imaging sensors. To precisely combine multisensory information, the rigid transformation between different sensor coordinate systems (i.e., extrinsic parameters) must be estimated. The majority of existing extrinsic calibration techniques require one or multiple planar calibration patterns (such as checkerboards) to be observed simultaneously from the range and imaging sensors. The main limitation of these approaches is that they require modifying the scene with artificial targets. In this paper, we present a novel algorithm for extrinsically calibrating a range sensor with respect to an image sensor with no requirement of external artificial targets. The proposed method exploits natural linear features in the scene to precisely determine the rigid transformation between the coordinate frames. First, a set of 3D lines (plane intersection and boundary line segments) are extracted from the point cloud, and a set of 2D line segments are extracted from the image. Correspondences between the 3D and 2D line segments are used as inputs to an optimization problem which requires jointly estimating the relative translation and rotation between the coordinate frames. The proposed method is not limited to any particular types or configurations of sensors. To demonstrate robustness, efficiency and generality of the presented algorithm, we include results using various sensor configurations.

Road direction detection based on vanishing-point tracking

We present a novel approach for vision-based road direction detection for autonomous Unmanned Ground Vehicles (UGVs). The proposed method utilizes only monocular vision information similar to human perception to detect road directions with respect to the vehicle. The algorithm searches for a global feature of the roads due to perspective projection (so-called vanishing point) to distinguish road directions. The proposed approach consists of two stages. The first stage estimates the vanishing-point locations from single frames. The second stage uses a Rao-Blackwellised particle filter to track initial vanishing-point estimations over a sequence of images in order to provide more robust estimation. Simultaneously, the direction of the road ahead of the vehicle is predicted, which is prerequisite information for vehicle steering and path planning. The proposed approach assumes minimum prior knowledge about the environment and can cope with complex situations such as ground cover variations, different illuminations, and cast shadows. Its performance is evaluated on video sequences taken during test run of the DARPA Grand Challenge.

Magnetic signatures in air for mobile devices

Recently, a new authentication method based on 3D signatures created in air is proposed for mobile devices [4]. The 3D signature is created in air using a properly shaped magnet (a rod or ring) taken in hand. It is based on influencing compass sensor embedded in the new generation of mobile devices. In this paper, we present implementation of this technology on a mobile device (iPhone 3GS). It can demonstrate authentication process using a gesture in the from of a 3D signature freely created in the space around the device by a magnet held in hand. Movement of the magnet in the from of a signature produces a temporal change in the magnetic field sensed by the embedded compass sensor, and can be used as a basis for authentication. As magnetic signatures are performed in 3D space, they can provide a wider choice for authentication, and they can not be easily hardcopied.

Assessing the vulnerability of magnetic gestural authentication to video-based shoulder surfing attacks

Secure user authentication on mobile phones is crucial, as they store highly sensitive information. Common approaches to authenticate a user on a mobile phone are based either on entering a PIN, a password, or drawing a pattern. However, these authentication methods are vulnerable to the shoulder surfing attack. The risk of this attack has increased since means for recording high-resolution videos are cheaply and widely accessible. If the attacker can videotape the authentication process, PINs, passwords, and patterns do not even provide the most basic level of security. In this project, we assessed the vulnerability of a magnetic gestural authentication method to the video-based shoulder surfing attack. We chose a scenario that is favourable to the attack-er. In a real world environment, we videotaped the interactions of four users performing magnetic signatures on a phone, in the presence of HD cameras from four different angles. We then recruited 22 participants and asked them to watch the videos and try to forge the signatures. The results revealed that with a certain threshold, i.e, th=1.67, none of the forging attacks was successful, whereas at this level all eligible login attempts were successfully recognized. The qualitative feedback also indicated that users found the magnetic gestural signature authentication method to be more secure than PIN-based and 2D signature methods.

Pingu: A New Miniature Wearable Device for Ubiquitous Computing Environments

Around Device Interaction (ADI) is recently introduced in the field of Human Computer Interaction (HCI)to provide touch less, more intuitive way of interaction using space beyond the physical boundary of the computing devices. In this paper, we introduce a new ADI input device called Pingu in the form factor of a fingering that allows users to interact with any nearby computing device with wireless connectivity in a ubiquitous environment. Fingering form factor is chosen for our prototype design, as it is socially acceptable and is commonly worn in everyday social contexts, and based on the previous research, the information entropy of interaction by fingers is greater than the entropy for any other parts of the human body. The current Pingu prototype is consisted of an extensive set of sensors, visual and vibrot actile feedback mechanisms with wireless connectivity that make it a unique input device for human-computer or human-human interaction in the form of gestures, tactile and touch. Its usage can range from advanced, tiny and novel gestural interaction with a variety of devices to mobile and networked sensing, and social computing. We present a few potential applications of Pingu such as social interaction, context recognition, in-car interaction, and physical activity analysis.

HeatWave: the next generation of thermography devices

Energy sustainability is a major challenge of the 21st century. To reduce environmental impact, changes are required not only on the supply side of the energy chain by introducing renewable energy sources, but also on the demand side by reducing energy usage and improving energy efficiency. Currently, 2D thermal imaging is used for energy auditing, which measures the thermal radiation from the surfaces of objects and represents it as a set of color-mapped images that can be analysed for the purpose of energy efficiency monitoring. A limitation of such a method for energy auditing is that it lacks information on the geometry and location of objects with reference to each other, particularly across separate images. Such a limitation prevents any quantitative analysis to be done, for example, detecting any energy performance changes before and after retrofitting. To address these limitations, we have developed a next generation thermography device called Heat Wave. Heat Wave is a hand-held 3D thermography device that consists of a thermal camera, a range sensor and color camera, and can be used to generate precise 3D model of objects with augmented temperature and visible information. As an operator holding the device smoothly waves it around the objects of interest, Heat Wave can continuously track its own pose in space and integrate new information from the range and thermal and color cameras into a single, and precise 3D multi-modal model. Information from multiple viewpoints can be incorporated together to improve the accuracy, reliability and robustness of the global model. The approach also makes it possible to reduce any systematic errors associated with the estimation of surface temperature from the thermal images.

Energetics-informed hexapod gait transitions across terrains

Legged robots offer the potential of locomotion across various types of terrains. Different terrains require different gait patterns to enable greater traversal efficiency. Consequently, as a legged robot transitions from one type of terrain to another, the gait pattern should be adapted so as to maximise traction and energy efficiency. This paper explores the use of power consumption as estimated by the robot in real-time for guiding this gait transition in the case of statically-stable locomotion. While moving, the robot autonomously assesses its power consumption, relates it to the traction, and switches between gaits so as to maximise efficiency. In this way, the robot only needs proprioceptive sensors and consequently does not require velocity estimation, ground imaging or profiling to maintain efficient locomotion across different terrains. The approach has been tested on a hexapod robot traversing a variety of terrain types and stiffness, including concrete, grass, mulch and leaf litter. The experimental results show that gait switching on energetics alone enables traction maintenance and efficient locomotion across different terrains. We also present comparisons between the power consumption metric used in this work and cost of transport which is used in the literature for characterising energetics for legged locomotion.

Real-time mobile 3D temperature mapping

The ability to measure surface temperature and represent it on a metrically accurate 3D model has proven applications in many areas, such as medical imaging, building energy auditing, and search and rescue. A system is proposed that enables this task to be performed with a handheld sensor, and for the first time with results able to be visualized and analyzed in real time. A device comprising a thermal-infrared camera and range sensor is calibrated geometrically and used for data capture. The device is localized using a combination of iterative closest point and video-based pose estimation from the thermal-infrared video footage, which is shown to reduce the occurrence of failure modes. Furthermore, the problem of misregistration, which can introduce severe distortions in assigned surface temperatures is avoided through the use of a risk-averse neighborhood weighting mechanism. Results demonstrate that the system is more stable and accurate than previous approaches, and can be used to accurately model complex objects and environments for practical tasks.

Real-Time Stabilisation for Hexapod Robots

Legged robots such as hexapod robots are capable of navigating in rough and unstructured terrain. When the terrain model is either known a priori or is observed by on-board sensors, motion planners can be used to give desired motion and stability for the robot. However, unexpected leg disturbances could occur due to inaccuracies of the model or sensors or simply due to the dynamic nature of the terrain. We provide a state space based framework for stabilisation of a high dimensional multi-legged robot which detects and recovers from unexpected events such as leg slip. We experimentally evaluate our approach using a modified PhantomX hexapod robot with extended tibia segments which significantly reduces its stability. Our results show that roll and pitch stability is improved by 2\(\times \) when using the proposed method.

Multi-sensor Finger Ring for Authentication Based on 3D Signatures

Traditional methods of authenticating a user, including password, a Personal Identification Number (PIN), or a more secure PIN entry method (A PIN entry method resilient against shoulder surfing [14]), can be stolen or accessed easily and, therefore, make the authentication unsecure. In this work, we present the usability of our multi-sensor based and standalone finger ring called Pingu in providing a highly secure access system. Specifically, Pingu allows users to make a 3D signature and record the temporal pattern of the signature via an advanced set of sensors. As a result, the user creates a 3D signature in air using his finger. Our approach has two main contributions: (1) Compared to other wearable devices, a finger ring is more socially acceptable, and (2) signatures created via a finger in the air or on a surface leaves no visible track and, thus, are extremely hard to forge. In other words, a 3D signature allows much higher flexibility in choosing a safe signature. Our experiment shows that the proposed hardware and methodology could result in a very high level of user authentication/identification performance.