Mobile locate on Meizu 15

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Category: Meizu Mobile

Figure 7 - uploaded by Daniel Wagner Content may be subject to copyright. View publication. Copy reference. Copy caption. Embed figure. Meizu M8 mobile phone front view, back view with mag- netic mounting ring, wide angle camera lens from AmacroX , mounted camera lens from upper left to lower right. Source publication. Wide Area Localization on Mobile Phones. Conference Paper. Full-text available.

Oct We present a fast and memory efficient method for localizing a mobile user's 6DOF pose from a single camera image.

Our approach registers a view with respect to a sparse 3D point reconstruction. The 3D point dataset is partitioned into pieces based on visibility constraints and occlusion culling, making it scalable and efficient to handle. Context in source publication. Context 1. The mobile phone and the setup are depicted in Figure 7. For simplicity, we calibrated the camera once with and without the AmacroX lens, but did not recalibrate the camera each time after reattaching the wide angle lens.

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View in full-text. By contrast, video-based localization [46, 5, 29,67] is applicable to both indoors and outdoors and has been shown to achieve sub-meter accuracy. However, video-based localization can be very compute-and storage intensive. Feb Abm Musa Jakob Eriksson. While the satellite-based Global Positioning System GPS is adequate for some outdoor applications, many other applications are held back by its multi-meter positioning errors and poor indoor coverage.

In this paper, we study the feasibility of real-time video-based localization on resource-constrained platforms. Before commencing a localization task, a video-based localization system downloads an offline model of a restricted target environment, such as a set of city streets, or an indoor shopping mall. The system is then able to localize the user within the model, using only video as input.

To enable such a system to run on resource-constrained embedded systems or smartphones, we a propose techniques for efficiently building a 3D model of a surveyed path, through frame selection and efficient feature matching, b substantially reduce model size by multiple compression techniques, without sacrificing localization accuracy, c propose efficient and concurrent techniques for feature extraction and matching to enable online localization, d propose a method with interleaved feature matching and optical flow based tracking to reduce the feature extraction and matching time in online localization.

Based on an extensive set of both indoor and outdoor videos, manually annotated with location ground truth, we demonstrate that sub-meter accuracy, at real-time rates, is achievable on smart-phone type platforms, despite challenging video conditions. Dec Imeen Ben salah. Visual Localization and Camera Pose Estimation. Recent progress in image-based localization techniques have led to methods that are robust to changes in scene appearance and illumination [7,57], scalable [36,53,54,79], and efficient [9, 15,18,28,30,[36][37][38]69].

Most localization approaches first recover putative matches between query image features and features associated with 3D structure. This raises significant privacy concerns when consumers use such services in their homes or in confidential industrial settings.

Even if only image features are uploaded, the privacy concerns remain as the images can be reconstructed fairly well from feature locations and descriptors. We propose to conceal the content of the query images from an adversary on the server or a man-in-the-middle intruder. The key insight is to replace the 2D image feature points in the query image with randomly oriented 2D lines passing through their original 2D positions.

It will be shown that this feature representation hides the image contents, and thereby protects user privacy, yet still provides sufficient geometric constraints to enable robust and accurate 6-DOF camera pose estimation from feature correspondences. Our proposed method can handle single-and multi-image queries as well as exploit additional information about known structure, gravity, and scale. Numerous experiments demonstrate the high practical relevance of our approach. Given a query image, the goal of visual localization problem is to estimate its camera pose, i.

Aug Visual localization is the problem of estimating a camera within a scene and a key component in computer vision applications such as self-driving cars and Mixed Reality. State-of-the-art approaches for accurate visual localization use scene-specific representations, resulting in the overhead of constructing these models when applying the techniques to new scenes.

Recently, deep learning-based approaches based on relative pose estimation have been proposed, carrying the promise of easily adapting to new scenes.

However, it has been shown such approaches are currently significantly less accurate than state-of-the-art approaches. In this paper, we are interested in analyzing this behavior. To this end, we propose a novel framework for visual localization from relative poses. Using a classical feature-based approach within this framework, we show state-of-the-art performance.

Replacing the classical approach with learned alternatives at various levels, we then identify the reasons for why deep learned approaches do not perform well. Based on our analysis, we make recommendations for future work. Place recognition techniques are also related to the visual localization problem as they can be used to determine which part of a scene might be visible in a query image Cao and Snavely ;Sattler et al.

As such, place recognition techniques are used to reduce the amount of data that has to be kept in RAM, as the regions visible in the retrieved images might be loaded from disk on demand Arth et al.

Yet, loading 3D points from disk results in high query latency. Large-scale, real-time visual-inertial localization revisited. Jun The overarching goals in image-based localization are scale, robustness and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both dominated the benchmarks and seen successful realworld deployment. They enable applications ranging from robot navigation, autonomous driving, virtual and augmented reality to device geo-localization.

Recently end-to-end learned localization approaches have been proposed which show promising results on small scale datasets.

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We aim to deploy localization at global-scale where one thus relies on methods using local features and sparse 3D models. Our approach spans from offline model building to real-time client-side pose fusion. The system compresses appearance and geometry of the scene for efficient model storage and lookup leading to scalability beyond what what has been previously demonstrated.

It allows for low-latency localization queries and efficient fusion run in real-time on mobile platforms by combining server-side localization with real-time visual-inertial-based camera pose tracking. In order to further improve efficiency we leverage a combination of priors, nearest neighbor search, geometric match culling and a cascaded pose candidate refinement step.

This combination outperforms previous approaches when working with large scale models and allows deployment at unprecedented scale. We demonstrate the effectiveness of our approach on a proof-of-concept system localizing 2. These matches are established by descriptor matching [21,37,39,59,63,68,69,81] or by regressing 3D coordinates from pixel patches [, 16, 23, 43, 46, 47, 65]. Memory cards allow you to expand the phone's built-in memory, A memory card sometimes called a flash memory card or a storage card is a small storage medium used to store data such as text, pictures, audio, and video, for use on small, portable or remote computing devices such as mobile phones, mp3 players, digital cameras.

Sensors Sensors are electronic components that detects and responds to some type of input from the physical environment. The specific input could be light, heat, motion, moisture, pressure and location, The output is generally a signal that is converted to use in computing systems, a location sensor, such as a GPS receiver is able to detect current location of your electronic device.

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Fingerprint front-mounted Accelerometer Gyro Proximity Compass. Capacity Battery Capacity is a measure typically in Amp-hr of the charge stored by the battery, and is determined by the mass of active material contained in the battery. The battery capacity represents the maximum amount of energy that can be extracted from the battery under certain conditions. Network 2G Network. LTE band 1 , 3 , 5 , 8 , 34 , 38 , 39 , 40 , 41 This allows the phone using the card to attach to a mobile network. Moving a SIM card from one phone to another allows a subscriber to switch mobile phones without having to contact their mobile network carrier.

SIM cards can also be used by a phone to store limited amounts of data, such as phone numbers and text messages. Connectivity USB.