Computer Vision Engineer

We are looking for a Computer Vision Engineer to contribute to the development of AI-driven video analytics solutions tailored for extracting detailed cricket data from various sources such as match footage, live broadcasts, and player tracking systems. In this role, you will be utilizing deep learning techniques, pose estimation algorithms, and image processing methodologies to scrutinize player movements, shot selection, bowling mechanics, and overall match dynamics. Your responsibilities will include: - Developing computer vision models geared towards player tracking, ball trajectory prediction, and shot classification within the realm of cricket analytics. - Extracting real-time insights from video streams, encompassing player positions, footwork analysis, and batting/bowling techniques. - Implementing pose estimation techniques (such as OpenPose, MediaPipe, DeepLabCut) to dissect player body movements. - Employing action recognition models to categorize batting strokes, bowling variations, and fielding plays. You will also be involved in: - Applying various deep learning tools like CNNs, Transformers, YOLO, Mask R-CNN, and Optical Flow for cricket action recognition. - Developing segmentation models to differentiate between players, umpires, and key match elements like the ball, stumps, and pitch zones. - Utilizing GANs and super-resolution techniques to enhance the quality of low-resolution video footage. - Constructing OCR systems for Optical Character Recognition to extract scoreboards and match statistics from live broadcasts. Additional responsibilities include: - Implementing real-time video processing pipelines using OpenCV, FFmpeg, and GStreamer. - Working with multi-angle TV footage and drone feeds to enrich match analysis. - Developing algorithms to ensure low-latency real-time detection of ball speed, swing, and spin. You will also be required to: - Create automated annotation tools for labeling cricket match videos. - Train supervised and unsupervised learning models using cricket datasets. - Collaborate with sports analysts to validate and refine model predictions. Furthermore, your duties will involve: - Deploying computer vision models on edge devices, cloud platforms, and real-time streaming systems. - Optimizing models for high accuracy and low latency in live cricket broadcasts. - Conducting A/B testing and continuous monitoring to enhance model performance. You will also be expected to: - Perform camera calibration for distortion correction and real-world coordinate mapping. - Implement homography transformation and perspective correction for multi-angle alignment. - Apply video trigonometry techniques to calculate player distances, ball speed, angles, and movement trajectories. - Work with multi-camera synchronization and stereo vision for depth estimation in cricket analytics. About the Company: Lifease Solutions LLP believes in the power of design and technology to address challenges and transform ideas into reality. As a prominent provider of software solutions and services, Lifease Solutions is dedicated to delivering innovative and high-quality solutions that drive growth and value for businesses. Headquartered in Noida, India, we specialize in the finance, sports, and capital market sectors, earning the trust of companies worldwide. Our track record showcases our capability to turn minor projects into major successes, and we continuously seek opportunities to help our clients optimize their IT investments.,