How Infosearch Supports AI and Computer Vision Companies?

The key ingredient of AI and computer vision companies is precisely labeled data. Infosearch BPO can help these companies, by transforming raw images, videos, text, audio and 3D sensor data into high-quality training data sets that can be used for machine-learning, image-recognition, autonomous-vehicle, robotics, and research apps.

Infosearch has a history of 15 annotation types and experience in both 2D and 3D data and serves as a specialised data-annotation partner for teams developing and enhancing their vision-based AI systems.

Annotation Services for Computer Vision

Infosearch offers the following core labelling techniques that are employed when training computer-vision models:

Bounding box annotation for object detection and location in images.
Polygon annotation for accurate object boundaries and pixel level shape definition.
Semantic segmentation of objects and regions in an image.
Facial recognition, pose estimation and landmark detection with keypoints and landmarks.
Image classification & tagging for organising visual data by categories.

These services enable computer vision teams with training of models for object detection, image recognition, scene understanding, medical imaging, quality inspection, and retail analytics applications.

Create video annotations for Dynamic AI Models

Computer vision does not necessarily need to rely on still photos. Infosearch also provides video annotation capabilities for object detection, localisation, tracking, human activity recognition, pose estimation and labelling, and provides labelled timestamps for events.

It can be used for video surveillance, action recognition, content indexing, sports analytics, retail behaviour analysis and autonomous systems.

3D LiDAR and Point Cloud Annotation

Infosearch offers 3D LiDAR and point cloud annotation for autonomous vehicles, robotics, mapping and smart city applications. It has the ability to detect 3D bounding boxes, label points, segment the semantic classes, segment the instances, classify the objects and track them.

Infosearch facilitates AI systems to understand environments in a 3D point cloud by labelling objects and providing spatial information, like vehicle, pedestrian, road, obstacle, and surrounding structure.

Support Across the AI Product Lifecycle

Infosearch collaborates with AI, machine-learning, computer-vision, autonomous-vehicle, robotics and research-lab groups requiring high quality, large-scale training data. It has the ability to help at various points in an AI project:

Data preparation: Structuring and annotating raw image, video, text, audio and sensor data.
Model training: Providing well-defined training data for supervised learning.
Model validation: To facilitate quality control and iterative modeling.
Scaling: Scaling out the capacity for annotations with growing data sets and product needs.

Industries Infosearch Serves

Infosearch’s expertise in annotation is useful to AI firms in industries including:

Robotics: Object recognition, understanding of the environment, and labelling of the sensor data.
Autonomous driving and automotive: LiDAR, camera, radar and sensor fusion datasets.
Healthcare and medical imaging: Medical annotation for AI-based diagnostics, research, etc.
Retail and e-commerce: Product recognition, visual search, shelf analytics, and customer-behaviour analysis.
Manufacturing: Aerial and drone imagery annotation in manufacturing.
Smart cities and mapping: Applying 3D point-cloud annotation to urban planning and geospatial applications.

Why AI Teams choose Infosearch?

AI Team Requirement	Infosearch Capability
Multiple data formats	Image, video, text, audio, LiDAR, 3D point-cloud annotation.
Precision labelling	Bounding boxes, polygons, segmentation, keypoints, cuboids, 3D annotation.
Scalable delivery	Scalability for expanding datasets and big AI projects.
Autonomous vehicles, robotics, healthcare, retail, agritech, research	Such are the varied domain-specific use cases.
Complete data support	Over 15 different types of annotations on 2D and 3D data.

A trustworthy Data Partner to drive AI Innovation

Creating strong AI models is not just about algorithms; it’s about having a consistent and well-labelled, domain-relevant data set. Infosearch can ease the strain of data annotation for AI and computer-vision firms without compromising the quality of this process that is crucial to reliable model performance.

From autonomous driving systems to robotics, medical imaging devices to retail analytics and everything in between, Infosearch offers the data-annotation infrastructure needed to take data from raw to production-ready AI.

Developing an AI or computer-visual product? Speak with Infosearch BPO about a customised data-annotation and AI training-data solution.