Object Detection

Object detection is a computer vision task that both locates and classifies objects within an image or video frame — producing bounding boxes around each object along with a class label and confidence score.

How It Works

Modern object detection runs in two broad styles:

1. Two-stage detectors (Faster R-CNN family) first propose regions likely to contain objects, then classify each region. Higher accuracy, slower.
2. One-stage detectors (YOLO, SSD, RetinaNet) predict bounding boxes and classes in a single forward pass. Faster, suitable for real-time video.

The typical pipeline:

• A convolutional backbone extracts visual features.
• A detection head predicts box coordinates and class probabilities at multiple scales.
• Non-maximum suppression removes overlapping duplicate detections.

Production systems achieve 30–60 FPS per camera on standard GPUs and commonly detect 80+ object classes out of the box.

Why It Matters

Object detection is the foundation for nearly every other video analytics task:

• Perimeter security — detect people or vehicles entering restricted zones.
• Retail analytics — count and classify shoppers vs. staff.
• Industrial safety — detect forklifts, spilled materials, or unprotected workers.
• Traffic intelligence — classify vehicles as cars, trucks, or buses for lane management.

IncoreSoft's Object Detection / Zone module turns any camera into a configurable zone monitor, triggering alerts when defined objects cross virtual boundaries.

Use Cases

• Abandoned object detection in airports and transit stations
• Loitering detection around ATMs and storefronts
• Vehicle classification on highways and at toll plazas
• Package and asset tracking in warehouses and yards
• Crowd density estimation at events and public spaces

Frequently Asked Questions

What's the difference between object detection and image classification?

Classification assigns one label to an entire image. Detection finds every object in the image, draws a box around it, and labels each one. Classification answers "is there a car?" — detection answers "where and how many?"

How accurate is object detection in real-world video?

On standard benchmarks, state-of-the-art models reach 50–60% mAP on 80+ classes. In narrow production use cases (a single object class under known camera conditions), accuracy commonly exceeds 95%.

Can object detection distinguish specific items like weapons or PPE?

Yes, with specialized training. IncoreSoft offers dedicated modules for gun detection and hard hat compliance rather than relying on generic 80-class models.