AI Image Processing

Face Recognition

HC Robotics stands out as an innovator with a robust suite of cutting-edge products. Our face recognition suite consists of advanced algorithms to extract the relevant information from the images for faster processing with high degree of accuracy.

HC Robotics uses DL (Deep Learning) models come out with rich and compact representations of faces to identify and classify them in a large dataset of faces. Our face recognition algorithms get better with time, and contribute to making life easier so that the consumer can focus on what matters the most.
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Features

  • Face detection and identification
  • Face count
  • Face registration using photo/video/live feed
  • User-defined threshold for face matching
  • User-friendly dashboard
  • Security alerts in case of intrusions
  • Automated smart analysis and reporting
  • Customized solution
  • Video analytics

Key Applications

  • Surveillance
  • Attendance automation
  • Instant generation of visitor pass

Gait RecognitionAI-based detection of a person based on physiological parameters

Recent studies in the field of video-based pose estimation have indicated to a large potential in using only two-dimensional video inputs for analyzing human Gait captured with cameras. Gait-based identification has become popular nowadays in view of its simplicity. Importantly, it can work remotely.

We have developed a robust workflow for analyzing the gait parameters and building an easy-to- train model. This can be used for building a data model on a custom dataset, comprising of lightweight hybrid neural networks along with a combination of CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), and LSTM (Long Short Term Memory) networks. We have considered the main factors such as accuracy and real-time processing and have built a system to deliver higher mean average precision on 4k resolution RGB images at minimum of 15 fps.
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Our neural networks-based gait recognition recognizes the physiological parameters such as built, height, and walking style of a person. Thereafter, these parameters are used for generating the gait patterns and identification of the person.

It is generally difficult to collect clear data of a moving object using a regular camera. This inaccuracy impacts the AI model accuracy and training.

We have custom-built camera with direct image data output, having the capability to capture fast-moving objects crystal clear, and at 15-20 fps rate with 4k resolution. Even objects at long distances can be captured clearly without losing much pixel information.

We provide a user-friendly dashboard to analyze real-time gait analysis, including custom-enhanced image like adjustment, contrast, and zoom in and zoom out of the region of interest, etc.

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