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العودة للرئيسية

كيف نحقق دقة قياس زمني ~4ms

phone لديه بالفعل كل ما يلزم لقياس سرعة عدو دقيق — كاميرا عالية معدل الإطارات، وجيروسكوب دقيق، ومعالج قوي. إليك ما يتيحه ذلك.

1

دقة دون الإطار

نادراً ما يعبر الرياضيون البوابة في اللحظة الدقيقة لالتقاط الإطار. يحلل نظامنا عدة إطارات لتحديد لحظة العبور بين الإطارات — محققاً دقة استيفاء دون الميلي ثانية تتجاوز بكثير الفاصل الزمني الأصلي للكاميرا.

The interpolation works by observing the athlete's torso position in at least 3 consecutive frames as they approach and cross the timing line. By fitting a linear motion model to these positions, we solve for the precise timestamp when the torso center crossed the gate position. Because human sprinting velocity is nearly constant over short distances (the 1-2 meter detection zone), the linear model produces highly accurate results.

2

تصحيحات مبنية على الفيزياء

تمسح كاميرات phone كل إطار من الأعلى إلى الأسفل خلال عدة ميلي ثوانٍ، مما يُدخل انحرافاً زمنياً حسب مكان ظهور الرياضي في الإطار. نصحح هذا تلقائياً إلى جانب آثار التوقيت الأخرى على مستوى العتاد لإزالة الخطأ المنهجي.

TrackSpeed automatically measures the rolling shutter duration for each device and applies a per-pixel timing correction. If an athlete's torso is detected at 40% of the frame height and the rolling shutter scan takes 10ms, we apply a 4ms correction to the timestamp. This correction is applied before interpolation, ensuring the trajectory regression operates on accurate timing data. The result: rolling shutter becomes a non-factor in the final timing.

3

مزامنة ساعة متعددة الأجهزة

عند استخدام جهازي phone — واحد عند البداية وآخر عند النهاية — يجب أن تتوافق ساعاتهما ضمن ميلي ثوانٍ. يحقق بروتوكول المزامنة لدينا محاذاة ±3-5ms بين الأجهزة. أثناء المزامنة، أبقِ الهاتفين على بعد 10 أمتار تقريباً للحصول على أفضل النتائج. بعد المزامنة، حرّكهما لأي مسافة تحتاجها.

The sync protocol sends multiple round-trip timing probes between the two phones via peer-to-peer WiFi. By measuring send and receive timestamps on both devices, we calculate the clock offset using the same mathematical principles as the Network Time Protocol (NTP). Multiple samples are taken and outliers are rejected, achieving ±3-5ms alignment between devices. During sync, keep both phones within about 10 meters of each other for best results. Once synced, move them as far apart as needed — the offset stays locked.

4

تتبع الجسم، لا كسر الشعاع

بوابات الليزر تنطلق عند أول ما يكسر الشعاع — ذراع ممدودة، ركبة، أو صدر. هذا يختلف حسب أسلوب الجري ويسبب عدم اتساق. يتتبع TrackSpeed كتلة جسم الرياضي لتحديد لحظة عبور جذعه الخط، مطابقاً لطريقة عمل القياس الرسمي.

TrackSpeed's detection engine replicates the official approach. Our geometry-based algorithm processes each video frame at 180×320 resolution, using frame differencing to detect motion, connected component labeling to identify body regions, and size/shape filters to isolate the torso from limbs. An arm-spike suppression algorithm prevents raised arms from triggering false crossings. The result: consistent chest-based timing that matches the official standard, unlike laser gates that trigger on the nearest body part.

~4ms
الدقة الزمنية الفعلية

الاستيفاء دون الإطار والتصحيحات الفيزيائية ومزامنة الساعة تتضافر لتقديم دقة قياس زمني تنافس الأجهزة المخصصة — باستخدام phone فقط.

كيف يقارن

النظامالدقةالكشفالتكلفة
FAT (رسمي)0.001sكاميرا صورة النهاية$10,000+
بوابات ليزر±50-200ms*أول كسر للشعاع$500-2000
TrackSpeed~4msتتبع الجسمphone
*بوابات الليزر تنطلق بسرعة دون الميلي ثانية، لكن نقاط التشغيل غير المتسقة (ذراع مقابل صدر) يمكن أن تسبب تباين 50-200ms بين محاولات نفس الرياضي.

The Detection Pipeline

Every video frame captured by your phone's camera goes through a multi-stage detection pipeline. Here's what happens in the roughly 2ms it takes to process each frame:

1. Downsample & Extract Luma

The raw camera frame is downsampled to 180×320 pixels and converted to a grayscale (luma) image. This resolution is sufficient for accurate body detection while keeping processing fast enough for real-time analysis at 120fps.

2. Frame Differencing

Each frame is compared against the previous frame (N-1 differencing). Pixels that changed significantly — above a fixed threshold of 15 — indicate motion. This produces a binary motion mask showing where the athlete is moving.

3. Connected Component Labeling

The motion mask is analyzed using an 8-connected component labeling algorithm, which groups adjacent motion pixels into distinct blobs. Each blob is a candidate body region.

4. Size & Shape Filters

Candidate blobs are filtered by physical plausibility. A valid body region must be at least 33% of the frame height and 8% of the frame width. Fill ratio (minimum 0.20) and aspect ratio (maximum 1.2) filters reject noise, shadows, and camera shake artifacts.

5. Gate Crossing Detection

When a validated body region crosses the timing line position, a crossing event is triggered. A 0.5-second cooldown prevents double-counting from the same athlete, and gate-occupied tracking ensures each crossing is recorded exactly once.

6. Position-Based Interpolation

The crossing timestamp is refined using trajectory regression across the surrounding frames. This is where the sub-frame precision comes from — converting a discrete frame event into a continuous-time measurement with ~4ms accuracy.

Device Stability & Thermal Management

Accurate detection requires a stable camera. TrackSpeed monitors your phone's gyroscope in real-time, alerting you if the device moves during timing. The IMU (Inertial Measurement Unit) detects rotation rates as small as 0.15 rad/s — about the level of vibration from a passing truck.

Running the camera at 120fps is computationally intensive. TrackSpeed continuously monitors the device's thermal state and will warn you if the phone is overheating, which can cause frame drops and reduce timing accuracy. For sessions longer than 30 minutes, we recommend using 60fps, which maintains ~6ms accuracy with significantly lower thermal impact.

Frequently Asked Questions

How accurate is phone-based sprint timing compared to laser gates?

TrackSpeed achieves ~4ms effective timing accuracy, which is more consistent than laser gates for training purposes. Laser gates have sub-millisecond trigger speed, but they trigger on whichever body part breaks the beam first — hand, knee, or chest — creating 50-200ms of run-to-run variability. TrackSpeed tracks the chest crossing, matching official timing standards and eliminating this inconsistency.

Does TrackSpeed work without internet or WiFi?

Yes. Single-phone timing works completely offline. Multi-phone timing uses peer-to-peer WiFi Direct between the devices — no internet connection or router needed. The phones connect directly to each other.

Can TrackSpeed replace professional timing equipment?

For training purposes, yes. TrackSpeed provides the consistency and accuracy needed to track progress, compare training sessions, and make coaching decisions. For official competition results that go on record, Fully Automatic Timing (FAT) systems with photo finish cameras remain the standard — they achieve 0.001s resolution. TrackSpeed is designed for the 99% of timing that happens in training, not the 1% that happens at meets.

Why does frame rate matter for timing accuracy?

Higher frame rates give more data points for trajectory regression. At 30fps, frames are 33.3ms apart; at 60fps, 16.7ms; at 120fps, 8.3ms. More frames near the crossing moment means better interpolation accuracy. However, even at 30fps, sub-frame interpolation achieves ~10ms accuracy — still far better than manual stopwatch timing (~200ms human reaction time error).

How does multi-phone timing work?

Place one phone at the start line and one at the finish. The phones connect via peer-to-peer WiFi and synchronize their clocks using an NTP-style protocol (±3-5ms accuracy). Each phone independently detects when the athlete crosses its line. The finish phone subtracts the start timestamp from the finish timestamp to calculate the elapsed time, corrected for the measured clock offset.

What happens if my phone overheats during a session?

TrackSpeed monitors thermal state and warns you before accuracy degrades. At 120fps, sustained recording can cause thermal throttling after 20-30 minutes, leading to dropped frames. If this happens, the app suggests switching to 60fps, which uses significantly less power while maintaining ~6ms timing accuracy. For long practice sessions, 60fps is recommended from the start.

مستعد لقياس تدريبك؟

حمّل TrackSpeed واختبر دقة الميلي ثانية بـ phone فقط.