However, blind users often tend to include their hand either interacting with the object that they wish to recognize or simply placing it in proximity for better camera aiming. Also, gaze information, commonly used to infer the area of interest in egocentric vision, is often not dependable. While we strive to improve recognition performance, it remains difficult to identify which object is of interest to the user the object may not even be included in the frame due to challenges in camera aiming without visual feedback. The study revealed that, compared to baseline RSA, the agents were significantly faster in providing navigational assistance to users, and their mental workload was significantly reduced - all indicate the feasibility and prospect of 3D maps in RSA.Д®gocentric vision holds great promises for increasing access to visual information and improving the quality of life for people with visual impairments, with object recognition being one of the daily challenges for this population. We conducted a walkthrough study with thirteen agents and one user with simulated vision impairment using this prototype. This paper presents a high-fidelity prototype of such an RSA, where agents use interactive 3D maps with localization capability. To address these challenges, researchers have suggested assisting agents with computer vision technologies, especially 3D reconstruction. Researchers found that agents' lack of environmental knowledge, the difficulty of orienting users in their surroundings, and the inability to estimate distances from users' camera feeds are key challenges to sighted agents. Remote sighted assistance (RSA) has emerged as a conversational assistive technology, where remote sighted workers, i.e., agents, provide real-time assistance to users with vision impairments via video-chat-like communication. A two-stage algorithm is presented that uses this information to guide users to the appropriate object interactively from their phone.

The request is first forwarded to remote workers who outline the object, enabling efficient and accurate automatic computer vision to guide users interactively from their existing cellphones. VizWiz::LocateIt enables blind people to take a picture and ask for assistance in finding a specific object.

In this paper we argue that many useful problems may be better solved by directly modeling them as search problems, and present a solution called VizWiz::LocateIt that directly supports this type of interaction.

Many tools seek to help blind people solve these problems by enabling them to query for additional information, such as color or text shown on the object. Text is pervasively used to label objects, colors carry special significance, and items can easily become lost in surroundings that cannot be quickly scanned. Blind people face a number of challenges when interacting with their environments because so much information is encoded visually.

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