This study investigates the potential of infrared (IR) camera technology to enhance driver safety for emergency vehicles operating in low-visibility conditions, particularly at night and in dense fog. Such environments significantly increase the risk of collisions, especially for tow trucks and snowplows that must remain operational in challenging conditions. Conventional driver assistance systems often struggle under these conditions due to limited visibility. In contrast, IR cameras, which detect the thermal signatures of obstacles, offer a promising alternative. The evaluation combines controlled laboratory experiments, real-world field tests, and surveys of emergency vehicle operators. In addition to assessing detection performance, the study examines the feasibility of retrofitting existing Department of Transportation (DoT) fleets with cost-effective IR-based driver assistance systems. Results underscore the utility of IR technology in enhancing driver awareness and provide data-driven recommendations for scalable deployment across legacy emergency vehicle fleets.

After months of anticipation, Apple finally unveiled its latest smartphone to the world last night. The iPhone 16e is Apple's latest'budget' smartphone, with prices starting at just 599/ 599. The new device runs Apple Intelligence features, including a ChatGPT integration with smart assistant Siri. It also includes a 6.1-inch display, a two-in-one camera system, an'extraordinary' battery life, and the return of the'notch' at the top of the display. While the focus has been on the new device, several eagle-eyed Apple fans have noticed that three popular devices have been quietly discontinued.

Products featured in this Shopping Finder article are selected by our shopping writers. If you make a purchase using links on this page, Dailymail.co.uk will earn an affiliate commission. After months of anticipation, Apple finally unveiled its latest smartphone to the world last night - the iPhone 16e. The device runs Apple Intelligence features, including a ChatGPT integration with smart assistant Siri. It also includes a 6.1-inch display, a two-in-one camera system, an'extraordinary' battery life, and the return of the'notch' at the top of the display.

Apple has finally pulled back the curtain on its latest'budget' smartphone – the iPhone 16e. Released February 28, the device runs Apple Intelligence features, including a ChatGPT integration with smart assistant Siri. It also has a 6.1-inch display, a two-in-one camera system, an'extraordinary' battery life, and sees the return of the'notch' at the top of the display. 'iPhone 16e packs in the features our users love about the iPhone 16 lineup, including breakthrough battery life, fast performance powered by the latest-generation A18 chip, an innovative 2-in-1 camera system, and Apple Intelligence,' said Kaiann Drance, Apple's vice president of worldwide iPhone product marketing. 'We're so excited for iPhone 16e to complete the lineup as a powerful, more affordable option to bring the iPhone experience to even more people.'

Generalizing metric monocular depth estimation presents a significant challenge due to its ill-posed nature, while the entanglement between camera parameters and depth amplifies issues further, hindering multi-dataset training and zero-shot accuracy. This challenge is particularly evident in autonomous vehicles and mobile robotics, where data is collected with fixed camera setups, limiting the geometric diversity. Y et, this context also presents an opportunity: the fixed relationship between the camera and the ground plane imposes additional perspective geometry constraints, enabling depth regression via vertical image positions of objects. However, this cue is highly susceptible to overfitting, thus we propose a novel canonical representation that maintains consistency across varied camera setups, effectively disentangling depth from specific parameters and enhancing generalization across datasets. W e also propose a novel architecture that adaptively and probabilistically fuses depths estimated via object size and vertical image position cues. A comprehensive evaluation demonstrates the effectiveness of the proposed approach on five autonomous driving datasets, achieving accurate metric depth estimation for varying resolutions, aspect ratios and camera setups. Notably, we achieve comparable accuracy to existing zero-shot methods, despite training on a single dataset with a single-camera setup.

This paper presents opt-in camera, a concept of privacy-preserving camera systems capable of recording only specific individuals in a crowd who explicitly consent to be recorded. Our system utilizes a mobile wireless communication tag attached to personal belongings as proof of opt-in and as a means of localizing tag carriers in video footage. Specifically, the on-ground positions of the wireless tag are first tracked over time using the unscented Kalman filter (UKF). The tag trajectory is then matched against visual tracking results for pedestrians found in videos to identify the tag carrier. Technically, we devise a dedicated trajectory matching technique based on constrained linear optimization, as well as a novel calibration technique that handles wireless tag-camera calibration and hyperparameter tuning for the UKF, which mitigates the non-line-of-sight (NLoS) issue in wireless localization. We realize the proposed opt-in camera system using ultra-wideband (UWB) devices and an off-the-shelf webcam installed in the environment. Experimental results demonstrate that our system can perform opt-in recording of individuals in near real-time at 10 fps, with reliable identification accuracy for a crowd of 8-23 people in a confined space.

The Pixel 9 Pro is a rare beast: a smaller phone that keeps the same bold design, specs and camera as Google's biggest and most expensive model. It makes it an instant contender for the best small phone going. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. At 999 ( 1,099/ 999/A 1,699), it is cheaper than its larger Pixel 9 Pro XL sibling but still firmly in the high-end bracket.

From the Ford Mustang to the Ford Focus, Ford has some of the most popular cars in the world. But Ford drivers be warned - your car could soon turn against you. That's according to a newly discovered patent, which suggests Ford is working on a way to allow your car to snitch on you for speeding. Among these challenges is a need to quickly and accurately identify a speeding vehicle and take responsive action,' the patent description reads. 'It is desirable to provide systems and methods that assist traffic police and/or other law enforcement officers perform such tasks.'

The Pixel 8a starts at 499 ( 549/ 499/A 849). That may be 50 more than last year's 7a, but the new model improves just about everything, and undercuts the Pixel 8 by 200. Google has revamped the design of the phone, giving it a more rounded shape, particularly at the corners, which makes it nicer to hold without a case. It is still unmistakably a Pixel, with a big aluminium camera bar across the back, and looks great in one of its more bold colours. The 6.1in screen has been upgraded from last year to match the more expensive Pixel 8, and is significantly brighter, running at up to 120Hz for smooth scrolling. It is a crisp and colourful display at a good size.

We propose an approach for reconstructing free-moving object from a monocular RGB video. Most existing methods either assume scene prior, hand pose prior, object category pose prior, or rely on local optimization with multiple sequence segments. We propose a method that allows free interaction with the object in front of a moving camera without relying on any prior, and optimizes the sequence globally without any segments. We progressively optimize the object shape and pose simultaneously based on an implicit neural representation. A key aspect of our method is a virtual camera system that reduces the search space of the optimization significantly. We evaluate our method on the standard HO3D dataset and a collection of egocentric RGB sequences captured with a head-mounted device. We demonstrate that our approach outperforms most methods significantly, and is on par with recent techniques that assume prior information.